@article{ ISI:000368959600007,
Author = {Desarkar, Maunendra Sankar and Sarkar, Sudeshna and Mitra, Pabitra},
Title = {{Preference relations based unsupervised rank aggregation for metasearch}},
Journal = {{EXPERT SYSTEMS WITH APPLICATIONS}},
Year = {{2016}},
Volume = {{49}},
Pages = {{86-98}},
Month = {{MAY 1}},
Abstract = {{Rank aggregation mechanisms have been used in solving problems from
   various domains such as bioinformatics, natural language processing,
   information retrieval, etc. Metasearch is one such application where a
   user gives a query to the metasearch engine, and the metasearch engine
   forwards the query to multiple individual search engines. Results or
   rankings returned by these individual search engines are combined using
   rank aggregation algorithms to produce the final result to be displayed
   to the user. We identify few aspects that should be kept in mind for
   designing any rank aggregation algorithm for metasearch. For example,
   generally equal importance is given to the input rankings while
   performing the aggregation. However, depending on the indexed set of web
   pages, features considered for ranking, ranking functions used etc. by
   the individual search engines, the individual rankings may be of
   different qualities. So; the aggregation algorithm should give more
   weight to the better rankings while giving less weight to others. Also,
   since the aggregation is performed when the user is waiting for
   response, the operations performed in the algorithm need to be light
   weight. Moreover, getting supervised data for rank aggregation problem
   is often difficult. In this paper, we present an unsupervised rank
   aggregation algorithm that is suitable for metasearch and addresses the
   aspects mentioned above. We also perform detailed experimental
   evaluation of the proposed algorithm on four different benchmark
   datasets having ground truth information. Apart from the unsupervised
   Kendall-Tau distance measure, several supervised evaluation measures are
   used for performance comparison. Experimental results demonstrate the
   efficacy of the proposed algorithm over baseline methods in terms of
   supervised evaluation metrics. Through these experiments we also show
   that Kendall-Tau distance metric may not be suitable for evaluating rank
   aggregation algorithms for metasearch. (C) 2015 Elsevier Ltd. All rights
   reserved.}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Desarkar, MS (Reprint Author), IIT Hyderabad, Kandi 502285, Telangana, India.
   Desarkar, Maunendra Sankar; Sarkar, Sudeshna; Mitra, Pabitra, IIT Kharagpur, Dept CSE, Kharagpur 721302, W Bengal, India.}},
DOI = {{10.1016/j.eswa.2015.12.005}},
ISSN = {{0957-4174}},
EISSN = {{1873-6793}},
Keywords = {{Rank aggregation; Metasearch; Information retrieval}},
Keywords-Plus = {{INFORMATION-RETRIEVAL; FUSION}},
Research-Areas = {{Computer Science; Engineering; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Engineering, Electrical \&
   Electronic; Operations Research \& Management Science}},
Author-Email = {{maunendra@iith.ac.in
   sudeshna@cse.iitkgp.ernet.in
   pabitra@cse.iitkgp.ernet.in}},
Funding-Acknowledgement = {{Microsoft Research, India}},
Funding-Text = {{Work of the first author is supported by a Ph.D. Fellowship from
   Microsoft Research, India.}},
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Number-of-Cited-References = {{70}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{14}},
Usage-Count-Since-2013 = {{14}},
Journal-ISO = {{Expert Syst. Appl.}},
Doc-Delivery-Number = {{DC1EM}},
Unique-ID = {{ISI:000368959600007}},
}

@article{ ISI:000370186000003,
Author = {Yun, Yong-Huan and Deng, Bai-Chuan and Cao, Dong-Sheng and Wang,
   Wei-Ting and Liang, Yi-Zeng},
Title = {{Variable importance analysis based on rank aggregation with applications
   in metabolomics for biomarker discovery}},
Journal = {{ANALYTICA CHIMICA ACTA}},
Year = {{2016}},
Volume = {{911}},
Pages = {{27-34}},
Month = {{MAR 10}},
Note = {{15th Conference on Chemometrics in Analytical Chemistry, Changsha,
   PEOPLES R CHINA, JUN 22-26, 2015}},
Abstract = {{Biomarker discovery is one important goal in metabolomics, which is
   typically modeled as selecting the most discriminating metabolites for
   classification and often referred to as variable importance analysis or
   variable selection. Until now, a number of variable importance analysis
   methods to discover biomarkers in the metabolomics studies have been
   proposed. However, different methods are mostly likely to generate
   different variable ranking results due to their different principles.
   Each method generates a variable ranking list just as an expert presents
   an opinion. The problem of inconsistency between different variable
   ranking methods is often ignored. To address this problem, a simple and
   ideal solution is that every ranking should be taken into account. In
   this study, a strategy, called rank aggregation, was employed. It is an
   indispensable tool for merging individual ranking lists into a single
   ``super{''}-list reflective of the overall preference or importance
   within the population. This ``super{''}-list is regarded as the final
   ranking for biomarker discovery. Finally, it was used for biomarkers
   discovery and selecting the best variable subset with the highest
   predictive classification accuracy. Nine methods were used, including
   three univariate filtering and six multivariate methods. When applied to
   two metabolic datasets (Childhood overweight dataset and
   Tubulointerstitial lesions dataset), the results show that the
   performance of rank aggregation has improved greatly with higher
   prediction accuracy compared with using all variables. Moreover, it is
   also better than penalized method, least absolute shrinkage and
   selectionator operator (LASSO), with higher prediction accuracy or less
   number of selected variables which are more interpretable. (C) 2016
   Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Liang, YZ (Reprint Author), Cent S Univ, Coll Chem \& Chem Engn, Changsha 410083, Hunan, Peoples R China.
   Yun, Yong-Huan; Wang, Wei-Ting; Liang, Yi-Zeng, Cent S Univ, Coll Chem \& Chem Engn, Changsha 410083, Hunan, Peoples R China.
   Deng, Bai-Chuan, South China Agr Univ, Coll Anim Sci, Guangzhou 510642, Guangdong, Peoples R China.
   Cao, Dong-Sheng, Cent S Univ, Coll Pharmaceut Sci, Changsha 410083, Hunan, Peoples R China.}},
DOI = {{10.1016/j.aca.2015.12.043}},
ISSN = {{0003-2670}},
EISSN = {{1873-4324}},
Keywords = {{Variable importance; Variable ranking; Biomarker discovery; Rank
   aggregation; Metabolomics}},
Keywords-Plus = {{PARTIAL LEAST-SQUARES; MODEL POPULATION ANALYSIS; WAVELENGTH INTERVAL
   SELECTION; MULTIVARIATE CALIBRATION; REGRESSION-MODELS; RANDOM FROG;
   OBESITY; CLASSIFICATION; ELIMINATION; OPTIMIZES}},
Research-Areas = {{Chemistry}},
Web-of-Science-Categories  = {{Chemistry, Analytical}},
Author-Email = {{yizeng\_liang@263.net}},
Cited-References = {{Wold S, 2001, CHEMOMETR INTELL LAB, V58, P109, DOI 10.1016/S0169-7439(01)00155-1.
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Number-of-Cited-References = {{46}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{0}},
Journal-ISO = {{Anal. Chim. Acta}},
Doc-Delivery-Number = {{DD8OI}},
Unique-ID = {{ISI:000370186000003}},
}

@article{ ISI:000366951100026,
Author = {Amodio, S. and D'Ambrosio, A. and Siciliano, R.},
Title = {{Accurate algorithms for identifying the median ranking when dealing with
   weak and partial rankings under the Kemeny axiomatic approach}},
Journal = {{EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}},
Year = {{2016}},
Volume = {{249}},
Number = {{2}},
Pages = {{667-676}},
Month = {{MAR 1}},
Abstract = {{Preference rankings virtually appear in all fields of science (political
   sciences, behavioral sciences, machine learning, decision making and so
   on). The well-known social choice problem consists in trying to find a
   reasonable procedure to use the aggregate preferences or rankings
   expressed by subjects to reach a collective decision. This turns out to
   be equivalent to estimate the consensus (central) ranking from data and
   it is known to be a NP-hard problem. A useful solution has been proposed
   by Emond and Mason in 2002 through the Branch-and-Bound algorithm (BB)
   within the Kemeny and Snell axiomatic framework. As a matter of fact, BB
   is a time demanding procedure when the complexity of the problem becomes
   untractable, i.e. a large number of objects, with weak and partial
   rankings, in presence of a low degree of consensus. As an alternative,
   we propose an accurate heuristic algorithm called FAST that finds at
   least one of the consensus ranking solutions found by BB saving a lot of
   computational time. In addition, we show that the building block of FAST
   is an algorithm called QUICK that finds already one of the BB solutions
   so that it can be fruitfully considered to speed up even more the
   overall searching procedure if the number of objects is low. Simulation
   studies and applications on real data allows to show the accuracy and
   the computational efficiency of our proposal. (C) 2015 Elsevier B.V. and
   Association of European Operational Research Societies (EURO) within the
   International Federation of Operational Research Societies (IFORS). All
   rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{D'Ambrosio, A (Reprint Author), Univ Naples Federico II, Dept Ind Engn, Naples, Italy.
   Amodio, S., Univ Naples Federico II, Dept Econ \& Stat, Naples, Italy.
   D'Ambrosio, A.; Siciliano, R., Univ Naples Federico II, Dept Ind Engn, Naples, Italy.}},
DOI = {{10.1016/j.ejor.2015.08.048}},
ISSN = {{0377-2217}},
EISSN = {{1872-6860}},
Keywords = {{Preference rankings; Median ranking; Kemeny distance; Social choice
   problem; Branch-and-bound algorithm}},
Keywords-Plus = {{PREFERENCE STRUCTURES; MODELS; CONSENSUS; CLASSIFICATION; DISTANCES;
   TREES}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
Author-Email = {{antdambr@unina.it}},
ResearcherID-Numbers = {{Amodio, Sonia/M-8739-2015
   D'Ambrosio, Antonio/L-9151-2015}},
ORCID-Numbers = {{Amodio, Sonia/0000-0001-6293-5491
   D'Ambrosio, Antonio/0000-0002-1905-037X}},
Funding-Acknowledgement = {{Progetto Innosystem, POR Campania FSE {[}CUP B25B09000070009]}},
Funding-Text = {{For Sonia Amodio this work was supported by Progetto Innosystem, POR
   Campania FSE 2007/2013, CUP B25B09000070009.}},
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Number-of-Cited-References = {{41}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{17}},
Usage-Count-Since-2013 = {{17}},
Journal-ISO = {{Eur. J. Oper. Res.}},
Doc-Delivery-Number = {{CZ2RA}},
Unique-ID = {{ISI:000366951100026}},
}

@article{ ISI:000371274400059,
Author = {Oliveira, Wendeson S. and Teixeira, Joyce Vitor and Ren, Tsang Ing and
   Cavalcanti, George D. C. and Sijbers, Jan},
Title = {{Unsupervised Retinal Vessel Segmentation Using Combined Filters}},
Journal = {{PLOS ONE}},
Year = {{2016}},
Volume = {{11}},
Number = {{2}},
Month = {{FEB 26}},
Abstract = {{Image segmentation of retinal blood vessels is a process that can help
   to predict and diagnose cardiovascular related diseases, such as
   hypertension and diabetes, which are known to affect the retinal blood
   vessels' appearance. This work proposes an unsupervised method for the
   segmentation of retinal vessels images using a combined matched filter,
   Frangi's filter and Gabor Wavelet filter to enhance the images. The
   combination of these three filters in order to improve the segmentation
   is the main motivation of this work. We investigate two approaches to
   perform the filter combination: weighted mean and median ranking.
   Segmentation methods are tested after the vessel enhancement. Enhanced
   images with median ranking are segmented using a simple threshold
   criterion. Two segmentation procedures are applied when considering
   enhanced retinal images using the weighted mean approach. The first
   method is based on deformable models and the second uses fuzzy C-means
   for the image segmentation. The procedure is evaluated using two public
   image databases, Drive and Stare. The experimental results demonstrate
   that the proposed methods perform well for vessel segmentation in
   comparison with state-of-the-art methods.}},
Publisher = {{PUBLIC LIBRARY SCIENCE}},
Address = {{1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Oliveira, WS (Reprint Author), Univ Fed Pernambuco, Ctr Informat, Recife, PE, Brazil.
   Oliveira, Wendeson S.; Teixeira, Joyce Vitor; Ren, Tsang Ing; Cavalcanti, George D. C., Univ Fed Pernambuco, Ctr Informat, Recife, PE, Brazil.
   Sijbers, Jan, Univ Antwerp, Dept Phys, IMinds Vis Lab, Antwerp, Belgium.}},
DOI = {{10.1371/journal.pone.0149943}},
Article-Number = {{e0149943}},
ISSN = {{1932-6203}},
Keywords-Plus = {{BLOOD-VESSELS; MATCHED-FILTERS; GRAY-LEVEL; IMAGES; CLASSIFICATION;
   EXTRACTION}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{wso@cin.ufpe.br}},
Funding-Acknowledgement = {{Fundacao de Amparo a Ciencia e Tecnologia do Estado de Pernambuco
   {[}IBPG-0152-1.03/12]; Conselho Nacional de Desenvolvimento Cientifico e
   Tecnologico; Coordenacao de Aperfeicoamento de Pessoal de Nivel
   Superior; Flemish Government Agency for Innovation by Science and
   Technology, Belgium through the SBO TOMFOOD project; CNPq; Capes; Facepe}},
Funding-Text = {{The sources of funding that have supported this work are: Fundacao de
   Amparo a Ciencia e Tecnologia do Estado de Pernambuco
   (http://www.facepe.br/), grant number IBPG-0152-1.03/12, author WSO;
   Conselho Nacional de Desenvolvimento Cientifico e Tecnologico
   (http://www.cnpq.br/), authors TIR, GDCC, JVT; Coordenacao de
   Aperfeicoamento de Pessoal de Nivel Superior (http://www.capes.gov.br/),
   authors TIR, GDCC; and Flemish Government Agency for Innovation by
   Science and Technology, Belgium through the SBO TOMFOOD project
   (http://www.iwt.be/), author JS. The funders had no role in study
   design, data collection and analysis, decision to publish, or
   preparation of the manuscript.; This work was partially supported by
   Brazilian agencies CNPq (Ciencias Sem Fronteiras), Capes, Facepe and by
   the Flemish Government Agency for Innovation by Science and Technology,
   Belgium through the SBO TOMFOOD project.}},
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Number-of-Cited-References = {{38}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{0}},
Journal-ISO = {{PLoS One}},
Doc-Delivery-Number = {{DF3UU}},
Unique-ID = {{ISI:000371274400059}},
}

@article{ ISI:000367756600014,
Author = {Jiang, Fan and Hu, Hai-Miao and Zheng, Jin and Li, Bo},
Title = {{A hierarchal BoW for image retrieval by enhancing feature salience}},
Journal = {{NEUROCOMPUTING}},
Year = {{2016}},
Volume = {{175}},
Number = {{A}},
Pages = {{146-154}},
Month = {{JAN 29}},
Abstract = {{Retrieving images with multiple features is an active research topic on
   boosting the performance of existing content-based image retrieval
   methods. The promising bags-of-words (BoW) models involve multiple
   features by applying feature fusion strategies in the early stage of
   image indexing. However, due to the different data forms of features, a
   simple joint may not guarantee a high retrieval performance. Moreover, a
   fused feature is not flexible enough to adapt to the variety of images.
   In order to avoid the submergence of feature salience, this letter
   proposes a hierarchal BoW to represent each feature in an individual
   codebook for obtaining the undisturbed ranks from each feature.
   Moreover, for feature salience enhancement, a query model based on
   ordinary-least-squared (OLS) regression is established for rank
   aggregation. The query model weighs each feature according to its
   retrieval performance and then selects the target images. The
   experimental results demonstrate that the proposed method improves the
   accuracy compared to the state-of-the-arts, meanwhile it maintains the
   stability. (C) 2015 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Hu, HM (Reprint Author), Beihang Univ, Sch Comp Sci \& Engn, Beijing Key Lab Digital Media, Beijing 100191, Peoples R China.
   Jiang, Fan; Hu, Hai-Miao; Zheng, Jin; Li, Bo, Beihang Univ, Sch Comp Sci \& Engn, Beijing Key Lab Digital Media, Beijing 100191, Peoples R China.
   Hu, Hai-Miao; Zheng, Jin; Li, Bo, Beihang Univ, State Key Lab Virtual Real Technol \& Syst, Beijing 100191, Peoples R China.}},
DOI = {{10.1016/j.neucom.2015.10.044}},
ISSN = {{0925-2312}},
EISSN = {{1872-8286}},
Keywords = {{Image retrieval; Hierarchal BoW; Feature salience enhancement; Query
   model}},
Keywords-Plus = {{FEATURE-SELECTION; FEATURE FUSION; INFORMATION-RETRIEVAL;
   CLASSIFICATION; MODEL; ALGORITHM}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{frank0139@163.com}},
Funding-Acknowledgement = {{National Natural Science Foundation of China {[}61370121]; National
   Hi-Tech Research and Development Program (863 Program) of China
   {[}2014AA015102]; Outstanding Tutors for Doctoral Dissertations of S\&T
   Project in Beijing {[}20131000602]}},
Funding-Text = {{This work was partially supported by the National Natural Science
   Foundation of China (No. 61370121), the National Hi-Tech Research and
   Development Program (863 Program) of China (No. 2014AA015102), and
   Outstanding Tutors for Doctoral Dissertations of S\&T Project in Beijing
   (No. 20131000602).}},
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Number-of-Cited-References = {{56}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Neurocomputing}},
Doc-Delivery-Number = {{DA4FX}},
Unique-ID = {{ISI:000367756600014}},
}

@article{ ISI:000367133700016,
Author = {Telcs, Andras and Kosztyan, Zsolt Tibor and Toeroek, Adam},
Title = {{Unbiased one-dimensional university ranking - application-based
   preference ordering}},
Journal = {{JOURNAL OF APPLIED STATISTICS}},
Year = {{2016}},
Volume = {{43}},
Number = {{1, SI}},
Pages = {{212-228}},
Month = {{JAN 2}},
Abstract = {{Our main goal is to produce a ranking technique which overcomes
   shortcomings of the numerous university rankings published. We propose a
   ranking method that provides a one-dimensional preference list of
   universities which is solely based on the partial rankings of
   applicants. Our ranking is free of subjective weights and uncomparable
   dimensions.}},
Publisher = {{TAYLOR \& FRANCIS LTD}},
Address = {{4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Telcs, A (Reprint Author), Budapest Univ Technol \& Econ, Dept Comp Sci \& Informat Theory, Magyar Tudosok Korutja 2, H-1117 Budapest, Hungary.
   Telcs, Andras, Budapest Univ Technol \& Econ, Dept Comp Sci \& Informat Theory, H-1117 Budapest, Hungary.
   Telcs, Andras; Kosztyan, Zsolt Tibor, Univ Pannonia, Fac Econ, Dept Quantitat Methods, H-8200 Veszprem, Hungary.
   Toeroek, Adam, Univ Pannonia, Fac Econ, Dept Econ, H-8200 Veszprem, Hungary.
   Toeroek, Adam, Budapest Univ Technol \& Econ, Fac Econ \& Social Sci, Dept Econ, H-1117 Budapest, Hungary.
   Toeroek, Adam, Hungarian Acad Sci, UP Joint Res Unit Reg Innovat \& Dev Studies, Budapest, Hungary.}},
DOI = {{10.1080/02664763.2014.998180}},
ISSN = {{0266-4763}},
EISSN = {{1360-0532}},
Keywords = {{university ranking; preference ordering; incomplete pairwise comparison;
   genetic algorithms; rank aggregation}},
Keywords-Plus = {{LEAGUE TABLES; LIMITATIONS}},
Research-Areas = {{Mathematics}},
Web-of-Science-Categories  = {{Statistics \& Probability}},
Author-Email = {{telcs@gtk.uni-pannon.hu}},
Funding-Acknowledgement = {{ {[}TaMOP-4.2.2/B-10/1-2010-0025]}},
Funding-Text = {{This paper was made under the project TaMOP-4.2.2/B-10/1-2010-0025. The
   authors are grateful to Andras Farkas for the elaborate explanation of
   linear ordering methods and several hints which proved to be essential
   in this work. Sincere thanks go to the team of FELVI.hu / Educatio Kht.
   for their help and authorization of usage of application data. We are
   indebted to several faculty members of University of Pannonia for their
   helpful comments and suggestions.}},
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Number-of-Cited-References = {{24}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{J. Appl. Stat.}},
Doc-Delivery-Number = {{CZ5HQ}},
Unique-ID = {{ISI:000367133700016}},
}

@article{ ISI:000364609900001,
Author = {Ebrahimnejad, Ali and Tavana, Madjid and Santos-Arteaga, Francisco J.},
Title = {{An integrated data envelopment analysis and simulation method for group
   consensus ranking}},
Journal = {{MATHEMATICS AND COMPUTERS IN SIMULATION}},
Year = {{2016}},
Volume = {{119}},
Pages = {{1-17}},
Month = {{JAN}},
Abstract = {{Group consensus ranking is an important topic in performance evaluation
   and selection research. Data envelopment analysis (DEA) has been used
   for obtaining an efficiency score (preference score) for each candidate.
   We propose an integrated DEA and simulation method for group consensus
   ranking. The ranking method proposed in this study has several unique
   features. In contrast to most voting methods that assume equal voting
   power to voters, the proposed method classifies voters into different
   groups and allows for assigning a different voting power to each group.
   In spite of its effectiveness, though similarly to the competing methods
   in the literature, the proposed method may lead to more than one
   efficient candidate. Several ranking models are extended and used to
   discriminate among the efficient candidates. Despite the wealth of
   information provided to the decision maker(s), different extended
   ranking models may produce different rankings. Simulation is used to
   analyze these rankings and synthesize them into one overall group
   ranking. A case study is used to demonstrate the applicability and
   exhibit the efficacy of the proposed method. (C) 2015 International
   Association for Mathematics and Computers in Simulation (IMACS).
   Published by Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Tavana, M (Reprint Author), La Salle Univ, Business Syst \& Analyt Dept, Distinguished Chair Business Analyt, Philadelphia, PA 19141 USA.
   Ebrahimnejad, Ali, Islamic Azad Univ, Qaemshahr Branch, Dept Math, Qaemshahr, Iran.
   Tavana, Madjid, La Salle Univ, Business Syst \& Analyt Dept, Distinguished Chair Business Analyt, Philadelphia, PA 19141 USA.
   Tavana, Madjid, Univ Paderborn, Fac Business Adm \& Econ, Business Informat Syst Dept, D-33098 Paderborn, Germany.
   Santos-Arteaga, Francisco J., Univ Complutense Madrid, Fac Econ, Dept Econ Aplicada 2, Pozuelo 28223, Spain.}},
DOI = {{10.1016/j.matcom.2015.08.022}},
ISSN = {{0378-4754}},
EISSN = {{1872-7166}},
Keywords = {{Data envelopment analysis; Simulation; Group ranking; Discrimination;
   Consensus}},
Keywords-Plus = {{RANKED VOTING SYSTEM; EFFICIENT CANDIDATES; COMMON-WEIGHTS; DEA; MODEL;
   UNITS; AGGREGATION; INFORMATION}},
Research-Areas = {{Computer Science; Mathematics}},
Web-of-Science-Categories  = {{Computer Science, Interdisciplinary Applications; Computer Science,
   Software Engineering; Mathematics, Applied}},
Author-Email = {{a.ebrahimnejad@srbiau.ac.ir
   tavana@lasalle.edu
   fransant@ucm.es}},
ORCID-Numbers = {{SANTOS ARTEAGA, Francisco Javier/0000-0003-2385-4781}},
Funding-Acknowledgement = {{office of vice-chancellor for research at Islamic Azad University,
   Qaemshahr Branch}},
Funding-Text = {{The first author appreciates the financial support he received from the
   office of vice-chancellor for research at Islamic Azad University,
   Qaemshahr Branch. The authors would also like to thank the anonymous
   reviewers and the editor-in-chief for their constructive comments and
   suggestion.}},
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Number-of-Cited-References = {{37}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{7}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{Math. Comput. Simul.}},
Doc-Delivery-Number = {{CV9LY}},
Unique-ID = {{ISI:000364609900001}},
}

@article{ ISI:000369539600003,
Author = {Kang, Guosheng and Liu, Jianxun and Tang, Mingdong and Cao, Buqing and
   Xu, Yu},
Title = {{An Effective Web Service Ranking Method via Exploring User Behavior}},
Journal = {{IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT}},
Year = {{2015}},
Volume = {{12}},
Number = {{4}},
Pages = {{554-564}},
Month = {{DEC}},
Abstract = {{Service-oriented computing and Web services are becoming more and more
   popular, enabling organizations to use the Web as a market for selling
   their own Web services and consuming existing Web services from others.
   Nevertheless, with the increasing adoption and presence of Web services,
   it becomes more difficult to find the most appropriate Web service that
   satisfies both users' functional and nonfunctional requirements. In this
   paper, we propose an effective Web service ranking approach based on
   collaborative filtering (CF) by exploring the user behavior, in which
   the invocation and query history are used to infer the potential user
   behavior. CF-based user similarity is calculated through similar
   invocations and similar queries (including functional query and QoS
   query) between users. Three aspects of Web services-functional
   relevance, CF based score, and QoS utility, are all considered for the
   final Web service ranking. To avoid the impact of different units,
   range, and distribution of variables, three ranks are calculated for the
   three factors respectively. The final Web service ranking is obtained by
   using a rank aggregation method based on rank positions. We also propose
   effective evaluation metrics to evaluate our approach. Large-scale
   experiments are conducted based on a real world Web service dataset.
   Experimental results show that the proposed approach outperforms the
   existing approach on the rank performance.}},
Publisher = {{IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC}},
Address = {{445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Kang, GS (Reprint Author), Fudan Univ, Sch Comp Sci, Shanghai Key Lab Data Sci, Shanghai 201203, Peoples R China.
   Kang, Guosheng, Fudan Univ, Sch Comp Sci, Shanghai Key Lab Data Sci, Shanghai 201203, Peoples R China.
   Liu, Jianxun; Tang, Mingdong; Cao, Buqing, Hunan Univ Sci \& Technol, Dept Comp Sci \& Engn, Xiangtan 411201, Peoples R China.
   Cao, Buqing, Wuhan Univ, State Key Lab Software Engn, Wuhan 430072, Peoples R China.
   Xu, Yu, Univ Dublin Trinity Coll, Sch Comp Sci, Dublin 2, Ireland.}},
DOI = {{10.1109/TNSM.2015.2499265}},
ISSN = {{1932-4537}},
Keywords = {{Web service; service ranking; functional relevance; collaborative
   filtering; QoS utility; user behavior}},
Keywords-Plus = {{DISCOVERY}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems}},
Author-Email = {{guoshengkang@gmail.com
   ljx529@gmail.com
   tangmingdong@gmail.com
   buqingcao@gmail.com
   xuyu1013@gmail.com}},
Cited-References = {{Alrifai M., 2010, P 19 INT C WORLD WID, P11, DOI 10.1145/1772690.1772693.
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Number-of-Cited-References = {{32}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{0}},
Journal-ISO = {{IEEE Trans. Netw. Serv. Manag.}},
Doc-Delivery-Number = {{DC9KE}},
Unique-ID = {{ISI:000369539600003}},
}

@article{ ISI:000368189000015,
Author = {Lorena, Luiz H. N. and Carvalho, Andre C. P. L. F. and Lorena, Ana C.},
Title = {{Filter Feature Selection for One-Class Classification}},
Journal = {{JOURNAL OF INTELLIGENT \& ROBOTIC SYSTEMS}},
Year = {{2015}},
Volume = {{80}},
Number = {{1, SI}},
Pages = {{S227-S243}},
Month = {{DEC}},
Abstract = {{In one-class classification problems all training examples belong to a
   single class. The absence of counter-examples represents a challenge to
   traditional Machine Learning and pre-processing techniques. This is the
   case of various feature selection techniques for labeled data. The
   selection of the most relevant features from a dataset usually benefits
   the performance obtained by classification algorithms. Despite the
   relevance of this issue, few techniques have been proposed for feature
   selection in one-class classification problems. Moreover, most of the
   existent techniques are wrapper approaches, which have to rely on a
   specific classification algorithm for feature selection, or aggregation
   techniques. This paper proposes a new filter feature selection approach
   for one-class classification. First, five feature selection measures
   from different paradigms are here employed or adapted to the one-class
   scenario. Next, the feature rankings produced by these measures are
   combined using different aggregation strategies. The proposed approach
   was able to reduce the size of the feature sets while maintaining or
   even improving the predictive performance obtained by the one-class
   classifier.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Lorena, LHN (Reprint Author), Univ Fed Sao Paulo UNIFESP, Inst Ciencia \& Tecnol, Sao Paulo, Brazil.
   Lorena, Luiz H. N.; Lorena, Ana C., Univ Fed Sao Paulo UNIFESP, Inst Ciencia \& Tecnol, Sao Paulo, Brazil.
   Carvalho, Andre C. P. L. F., Univ Sao Paulo, Inst Ciencias Matemat \& Comp, Sao Paulo, Brazil.}},
DOI = {{10.1007/s10846-014-0101-2}},
ISSN = {{0921-0296}},
EISSN = {{1573-0409}},
Keywords = {{Filter feature selection; Rank aggregation; One-class classification}},
Keywords-Plus = {{NOVELTY DETECTION; ALGORITHMS; PREDICTION; SUPPORT}},
Research-Areas = {{Computer Science; Robotics}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Robotics}},
Author-Email = {{luiz-lorena@hotmail.com
   aclorena@unifesp.br
   andre@icmc.usp.br}},
ResearcherID-Numbers = {{Cepid, CeMEAI/J-2417-2015}},
Funding-Acknowledgement = {{Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES);
   Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq);
   Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)}},
Funding-Text = {{The authors would like to thank the Coordenacao de Aperfeicoamento de
   Pessoal de Nivel Superior (CAPES), the Conselho Nacional de
   Desenvolvimento Cientifico e Tecnologico (CNPq) and the Fundacao de
   Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) for their financial
   support.}},
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Number-of-Cited-References = {{46}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{J. Intell. Robot. Syst.}},
Doc-Delivery-Number = {{DB0HK}},
Unique-ID = {{ISI:000368189000015}},
}

@article{ ISI:000365803600010,
Author = {Lazic, Stanley E.},
Title = {{Ranking, selecting, and prioritising genes with desirability functions}},
Journal = {{PEERJ}},
Year = {{2015}},
Volume = {{3}},
Month = {{NOV 26}},
Abstract = {{In functional genomics experiments, researchers often select genes to
   follow-up or validate from a long list of differentially expressed
   genes. Typically, sharp thresholds are used to bin genes into groups
   such as significant/non-significant or fold change above/below a cut-off
   value, and ad hoc criteria are also used such as favouring well-known
   genes. Binning, however, is inefficient and does not take the
   uncertainty of the measurements into account. Furthermore, p-values,
   fold-changes, and other outcomes are treated as equally important, and
   relevant genes may be overlooked with such an approach. Desirability
   functions are proposed as a way to integrate multiple selection criteria
   for ranking, selecting, and prioritising genes. These functions map any
   variable to a continuous 0-1 scale, where one is maximally desirable and
   zero is unacceptable. Multiple selection criteria are then combined to
   provide an overall desirability that is used to rank genes. In addition
   to p-values and fold-changes, further experimental results and
   information contained in databases can be easily included as criteria.
   The approach is demonstrated with a breast cancer microarray data set.
   The functions and an example data set can be found in the desiR package
   on CRAN (https://cran.r-project.org/web/packages/desiR/) and the
   development version is available on GitHub
   (https://github.com/stanlazic/desiR).}},
Publisher = {{PEERJ INC}},
Address = {{341-345 OLD ST, THIRD FLR, LONDON, EC1V 9LL, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Lazic, SE (Reprint Author), Novartis Inst Biomed Res, Silico Lead Discovery, Basel, Switzerland.
   Lazic, Stanley E., Novartis Inst Biomed Res, Silico Lead Discovery, Basel, Switzerland.}},
DOI = {{10.7717/peerj.1444}},
Article-Number = {{e1444}},
ISSN = {{2167-8359}},
Keywords = {{Desirability; Gene expression; Microarray; Data fusion; Rank aggregation}},
Keywords-Plus = {{EPITHELIAL-MESENCHYMAL TRANSITION; BREAST-CANCER CELLS; MICROARRAY
   EXPERIMENTS; AGGREGATION APPROACH; VARIABLES; DICHOTOMIZATION;
   CATEGORIZATION; OPTIMIZATION; METAANALYSIS; INTEGRATION}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{stan.lazic@cantab.net}},
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Number-of-Cited-References = {{32}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{PeerJ}},
Doc-Delivery-Number = {{CX6IE}},
Unique-ID = {{ISI:000365803600010}},
}

@article{ ISI:000361411200015,
Author = {Abel, Edward and Mikhailov, Ludmil and Keane, John},
Title = {{Group aggregation of pairwise comparisons using multi-objective
   optimization}},
Journal = {{INFORMATION SCIENCES}},
Year = {{2015}},
Volume = {{322}},
Pages = {{257-275}},
Month = {{NOV 20}},
Abstract = {{In group decision making, multiple decision makers (DMs) aim to reach a
   consensus ranking of alternatives in a decision problem. The differing
   expertise, experience and, potentially conflicting, interests of the DMs
   will result in the need for some form of conciliation to achieve
   consensus. Pairwise comparisons are commonly used to elicit values of
   preference of a DM. The aggregation of the preferences of multiple DMs
   must additionally consider potential conflict between DMs and how these
   conflicts may result in a need for compromise to reach group consensus.
   We present an approach to aggregating the preferences of multiple DMs,
   utilizing multi-objective optimization, to derive and highlight
   underlying conflict between the DMs when seeking to achieve consensus.
   Extracting knowledge of conflict facilitates both traceability and
   transparency of the trade-offs involved when reaching a group consensus.
   Further, the approach incorporates inconsistency reduction during the
   aggregation process to seek to diminish adverse effects upon decision
   outcomes. The approach can determine a single final solution based on
   either global compromise information or through utilizing weights of
   importance of the DMs.
   Within multi-criteria decision making, we present a case study within
   the Analytical Hierarchy Process from which we derive a richer final
   ranldng of the decision alternatives. (C) 2015 Published by Elsevier
   Inc.}},
Publisher = {{ELSEVIER SCIENCE INC}},
Address = {{360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Abel, E (Reprint Author), Univ Manchester, Sch Comp Sci, Manchester M13 9PL, Lancs, England.
   Abel, Edward; Keane, John, Univ Manchester, Sch Comp Sci, Manchester M13 9PL, Lancs, England.
   Mikhailov, Ludmil, Univ Manchester, Manchester Business Sch, Manchester M15 6PB, Lancs, England.}},
DOI = {{10.1016/j.ins.2015.05.027}},
ISSN = {{0020-0255}},
EISSN = {{1872-6291}},
Keywords = {{Group decision making; Pairwise comparison; Multi-criteria decision
   making; Inconsistency; Multi-objective optimization; Genetic algorithm}},
Keywords-Plus = {{ANALYTIC HIERARCHY PROCESS; COMPARISON MATRICES; JUDGMENTS; PRIORITIES;
   AHP}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems}},
Author-Email = {{edabelcs@gmail.com}},
ORCID-Numbers = {{Mikhailov, Ludmil/0000-0001-7172-7731}},
Funding-Acknowledgement = {{Engineering and Physical Science Research Council (EPSRC)}},
Funding-Text = {{Abel acknowledges the support of the Engineering and Physical Science
   Research Council (EPSRC) via their doctoral training grant.}},
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Number-of-Cited-References = {{33}},
Times-Cited = {{3}},
Usage-Count-(Last-180-days) = {{14}},
Usage-Count-Since-2013 = {{14}},
Journal-ISO = {{Inf. Sci.}},
Doc-Delivery-Number = {{CR5UZ}},
Unique-ID = {{ISI:000361411200015}},
}

@article{ ISI:000366113200045,
Author = {Chen, XiangJian and Shi, KeQing and Wang, YuQun and Song, Mei and Zhou,
   Wu and Tu, HongXiang and Lin, Zhuo},
Title = {{Clinical value of integrated-signature miRNAs in colorectal cancer:
   miRNA expression profiling analysis and experimental validation}},
Journal = {{ONCOTARGET}},
Year = {{2015}},
Volume = {{6}},
Number = {{35}},
Pages = {{37553-37565}},
Month = {{NOV 10}},
Abstract = {{MicroRNA (miRNA) expression profiling of colorectal cancer (CRC) are
   often inconsistent among different studies. To determine candidate miRNA
   biomarkers for CRC, we performed an integrative analysis of miRNA
   expression profiling compared CRC tissues and paired neighboring
   noncancerous colorectal tissues. Using robust rank aggregation method,
   we identified a miRNA set of 10 integrated-signature miRNAs. In
   addition, the qRT-PCR validation demonstrated that 9 miRNAs were
   consistent dysregulated with the integrative analysis in CRC tissues, 4
   miRNAs (miR-21-5p, miR-183-5p, miR-17-5p and miR-20a-5p) were
   up-regulated expression, and 5 miRNAs (miR-145-5p, miR-195-5p,
   miR-139-5p, miR-378a-5p and miR-143-3p) were down-regulated expression
   (all p < 0.05). Consistent with the initial analysis, 7 miRNAs were
   found to be significantly dysregulated in CRC tissues in TCGA data base,
   4 miRNAs (miR-21-5p, miR-183-5p, miR-17-5p and miR-20a-5p) were
   significantly up-regulated expression, and 3 miRNAs (miR-145-5p,
   miR-139-5p and miR-378a-5p) were significantly down-regulated expression
   in CRC tissues (all p < 0.001). Furthermore, miR-17-5p (p = 0.011) and
   miR-20a-5p (p = 0.003) were up-regulated expression in the III/IV tumor
   stage, miR-145-5p (p = 0.028) and miR-195-5p (p = 0.001) were
   significantly increased expression with microscopic vascular invasion in
   CRC tissues, miR-17-5p (p = 0.037) and miR-145-5p (p = 0.023) were
   significantly increased expression with lymphovascular invasion.
   Moreover, Cox regression analysis of CRC patients in TCGA data base
   showed miR-20a-5p was correlated with survival (hazard ratio: 1.875,
   95\% CI: 1.088-3.232, p = 0.024). Hence, the finding of current study
   provides a basic implication of these miRNAs for further clinical
   application in CRC.}},
Publisher = {{IMPACT JOURNALS LLC}},
Address = {{6211 TIPTON HOUSE, STE 6, ALBANY, NY 12203 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Lin, Z (Reprint Author), Wenzhou Med Univ, Affiliated Hosp 1, Liver Res Ctr, Dept Infect \& Liver Dis, Wenzhou, Zhejiang, Peoples R China.
   Chen, XiangJian, Wenzhou Med Univ, Affiliated Hosp 1, Dept Endoscop Surg, Wenzhou, Zhejiang, Peoples R China.
   Shi, KeQing; Wang, YuQun; Song, Mei; Lin, Zhuo, Wenzhou Med Univ, Affiliated Hosp 1, Liver Res Ctr, Dept Infect \& Liver Dis, Wenzhou, Zhejiang, Peoples R China.
   Zhou, Wu; Tu, HongXiang, Wenzhou Med Univ, Affiliated Hosp 1, Dept Lab Med, Wenzhou, Zhejiang, Peoples R China.}},
ISSN = {{1949-2553}},
Keywords = {{colorectal cancer; microRNA; signature; biomarker; robust rank
   aggregation}},
Keywords-Plus = {{MICRORNA EXPRESSION; COLON-CANCER; RECTAL-CANCER; TUMOR-GROWTH;
   DIFFERENTIAL EXPRESSION; BIOMARKER DISCOVERY; MIR-17-92 CLUSTER;
   NODE-METASTASIS; IDENTIFICATION; MIR-21}},
Research-Areas = {{Oncology; Cell Biology}},
Web-of-Science-Categories  = {{Oncology; Cell Biology}},
Author-Email = {{biolinz@163.com}},
Funding-Acknowledgement = {{Science and Technology Project of Wenzhou {[}Y20140718]; Incubator
   Program of the First Affiliated Hospital of Wenzhou Medical University
   {[}FHY2014038]}},
Funding-Text = {{This work was supported by grants from the Science and Technology
   Project of Wenzhou (Y20140718) and Incubator Program of the First
   Affiliated Hospital of Wenzhou Medical University (FHY2014038).}},
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Number-of-Cited-References = {{55}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Oncotarget}},
Doc-Delivery-Number = {{CY0RL}},
Unique-ID = {{ISI:000366113200045}},
}

@article{ ISI:000362454400002,
Author = {Leyva Lopez, Juan C. and Alvarez Carrillo, Pavel A.},
Title = {{Accentuating the rank positions in an agreement index with reference to
   a consensus order}},
Journal = {{INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH}},
Year = {{2015}},
Volume = {{22}},
Number = {{6}},
Pages = {{969-995}},
Month = {{NOV}},
Abstract = {{In this paper, we propose an index that measures the agreement level
   between an individual opinion and a collective opinion when both are
   expressed by rankings of a set of alternatives. This index constitutes
   an interesting weighted version of the well-known Kendall's ranks
   correlation index. The originality of the proposed index arises from the
   fact that it accounts for the relevance of the specific position of the
   alternatives in an individual order to quantify the agreement level of
   the individual order with respect to a collective temporary order. The
   paper also introduces a new consensus measure model. The core of the
   consensus model is the proposed agreement index. We present an
   illustrative example to describe the consensus process. We can obtain a
   faster convergence to a consensus solution using this new index compared
   to Kendall's index.}},
Publisher = {{WILEY-BLACKWELL}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Lopez, JCL (Reprint Author), Univ Occidente, Culiacan, Sinaloa, Mexico.
   Leyva Lopez, Juan C.; Alvarez Carrillo, Pavel A., Univ Occidente, Culiacan, Sinaloa, Mexico.
   Leyva Lopez, Juan C., Univ Autonoma Sinaloa, Culiacan, Mexico.}},
DOI = {{10.1111/itor.12146}},
ISSN = {{0969-6016}},
EISSN = {{1475-3995}},
Keywords = {{group decision support systems; group multicriteria decision aid;
   consensus ranking; agreement level; Kendall's distance; relative
   importance rank positions; interactive decision aid}},
Keywords-Plus = {{GROUP DECISION-SUPPORT; DISTANCE; MODELS}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
Author-Email = {{juan.leyva@udo.mx
   pavel.alvarez@udo.mx}},
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   Yilmaz E., 2008, SIGIR 08, P587.}},
Number-of-Cited-References = {{36}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Int. Trans. Oper. Res.}},
Doc-Delivery-Number = {{CS9ZW}},
Unique-ID = {{ISI:000362454400002}},
}

@article{ ISI:000363160100046,
Author = {Shi, Ke-Qing and Lin, Zhuo and Chen, Xiang-Jian and Song, Mei and Wang,
   Yu-Qun and Cai, Yi-Jing and Yang, Nai-Bing and Zheng, Ming-Hua and Dong,
   Jin-Zhong and Zhang, Lei and Chen, Yong-Ping},
Title = {{Hepatocellular carcinoma associated microRNA expression signature:
   integrated bioinformatics analysis, experimental validation and clinical
   significance}},
Journal = {{ONCOTARGET}},
Year = {{2015}},
Volume = {{6}},
Number = {{28}},
Pages = {{25093-25108}},
Month = {{SEP 22}},
Abstract = {{microRNA (miRNA) expression profiles varied greatly among current
   studies due to different technological platforms and small sample size.
   Systematic and integrative analysis of published datesets that compared
   the miRNA expression profiles between hepatocellular carcinoma (HCC)
   tissue and paired adjacent noncancerous liver tissue was performed to
   determine candidate HCC associated miRNAs. Moreover, we further
   validated the confirmed miRNAs in a clinical setting using qRT-PCR and
   Tumor Cancer Genome Atlas (TCGA) dataset. A miRNA integrated-signature
   of 5 upregulated and 8 downregulated miRNAs was identified from 26
   published datesets in HCC using robust rank aggregation method. qRT-PCR
   demonstrated that miR-93-5p, miR-224-5p, miR-221-3p and miR-21-5p was
   increased, whereas the expression of miR-214-3p, miR-199a-3p,
   miR-195-5p, miR-150-5p and miR-145-5p was decreased in the HCC tissues,
   which was also validated on TCGA dataset. A miRNA based score using
   LASSO regression model provided a high accuracy for identifying HCC
   tissue (AUC = 0.982): HCC risk score = 0.180E\_miR-221 + 0.0262E\_miR-21
   -0.007E\_miR-223 - 0.185E\_miR-130a. E\_miR-n = Log 2 (expression of
   microRNA n). Furthermore, expression of 5 miRNAs (miR-222, miR-221,
   miR-21 miR-214 and miR-130a) correlated with pathological tumor grade.
   Cox regression analysis showed that miR-21 was related with 3-year
   survival (hazard ratio {[}HR]: 1.509, 95\% CI: 1.079-2.112, P = 0.016)
   and 5-year survival (HR: 1.416, 95\% CI: 1.057-1.897, P = 0.020).
   However, none of the deregulated miRNAs was related with microscopic
   vascular invasion. This study provides a basis for further clinical
   application of miRNAs in HCC.}},
Publisher = {{IMPACT JOURNALS LLC}},
Address = {{6211 TIPTON HOUSE, STE 6, ALBANY, NY 12203 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Chen, YP (Reprint Author), Wenzhou Med Univ, Affiliated Hosp 1, Liver Res Ctr, Dept Infect \& Liver Dis, Wenzhou 325000, Zhejiang, Peoples R China.
   Shi, Ke-Qing; Lin, Zhuo; Song, Mei; Wang, Yu-Qun; Cai, Yi-Jing; Yang, Nai-Bing; Zheng, Ming-Hua; Dong, Jin-Zhong; Zhang, Lei; Chen, Yong-Ping, Wenzhou Med Univ, Affiliated Hosp 1, Liver Res Ctr, Dept Infect \& Liver Dis, Wenzhou 325000, Zhejiang, Peoples R China.
   Chen, Xiang-Jian, Wenzhou Med Univ, Affiliated Hosp 1, Dept Gen Surg, Wenzhou 325000, Zhejiang, Peoples R China.}},
DOI = {{10.18632/oncotarget.4437}},
ISSN = {{1949-2553}},
Keywords = {{hepatocellular carcinoma; microRNA; biomarker; signature; robust rank
   aggregation}},
Keywords-Plus = {{ROBUST RANK AGGREGATION; NON-TUMOROUS TISSUES; UP-REGULATION; MICROARRAY
   ANALYSIS; COLORECTAL-CANCER; DOWN-REGULATION; IN-VITRO; HEPATITIS;
   IDENTIFICATION; METAANALYSIS}},
Research-Areas = {{Oncology; Cell Biology}},
Web-of-Science-Categories  = {{Oncology; Cell Biology}},
Author-Email = {{ypchen1959@163.com}},
ORCID-Numbers = {{Zheng, Ming-Hua/0000-0003-4984-2631}},
Funding-Acknowledgement = {{Scientific Research Foundation of Wenzhou, Zhejiang Province, China
   {[}Y2013073, Y20120183]; Incubator program of the First Affiliated
   Hospital of Wenzhou Medical University {[}HFY2014050]}},
Funding-Text = {{This work was supported by grants from the Scientific Research
   Foundation of Wenzhou, Zhejiang Province, China (Y2013073, Y20120183)
   and Incubator program of the First Affiliated Hospital of Wenzhou
   Medical University (HFY2014050).}},
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Number-of-Cited-References = {{52}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Oncotarget}},
Doc-Delivery-Number = {{CT9TS}},
Unique-ID = {{ISI:000363160100046}},
}

@article{ ISI:000364541000024,
Author = {Wang, Hou-Ling and Li, Lan and Tang, Sha and Yuan, Chao and Tian,
   Qianqian and Su, Yanyan and Li, Hui-Guang and Zhao, Lin and Yin, Weilun
   and Zhao, Rui and Xia, Xinli},
Title = {{Evaluation of Appropriate Reference Genes for Reverse
   Transcription-Quantitative PCR Studies in Different Tissues of a Desert
   Poplar via Comparision of Different Algorithms}},
Journal = {{INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES}},
Year = {{2015}},
Volume = {{16}},
Number = {{9}},
Pages = {{20468-20491}},
Month = {{SEP}},
Abstract = {{Despite the unshakable status of reverse transcription-quantitative PCR
   in gene expression analysis, it has certain disadvantages, including
   that the results are highly dependent on the reference genes selected
   for data normalization. Since inappropriate endogenous control genes
   will lead to inaccurate target gene expression profiles, the validation
   of suitable internal reference genes is essential. Given the increasing
   interest in functional genes and genomics of Populus euphratica, a
   desert poplar showing extraordinary adaptation to salt stress, we
   evaluated the expression stability of ten candidate reference genes in
   P. euphratica roots, stems, and leaves under salt stress conditions. We
   used five algorithms, namely, C-t, NormFinder, geNorm, GrayNorm, and a
   rank aggregation method (RankAggreg) to identify suitable normalizers.
   To support the suitability of the identified reference genes and to
   compare the relative merits of these different algorithms, we analyzed
   and compared the relative expression levels of nine P. euphratica
   functional genes in different tissues. Our results indicate that a
   combination of multiple reference genes recommended by GrayNorm
   algorithm (e.g., a combination of Actin, EF1, GAPDH, RP, UBQ in root)
   should be used instead of a single reference gene. These results are
   valuable for research of gene identification in different P. euphratica
   tissues.}},
Publisher = {{MDPI AG}},
Address = {{POSTFACH, CH-4005 BASEL, SWITZERLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Zhao, R (Reprint Author), Beijing Forestry Univ, Coll Biol Sci \& Technol, Natl Engn Lab Tree Breeding, Beijing 100083, Peoples R China.
   Wang, Hou-Ling; Li, Lan; Yuan, Chao; Tian, Qianqian; Su, Yanyan; Li, Hui-Guang; Zhao, Lin; Yin, Weilun; Zhao, Rui; Xia, Xinli, Beijing Forestry Univ, Coll Biol Sci \& Technol, Natl Engn Lab Tree Breeding, Beijing 100083, Peoples R China.
   Wang, Hou-Ling; Yin, Weilun, Beijing Forestry Univ, Coll Forestry, Minist Educ, Key Lab Silviculture \& Conservat, Beijing 100083, Peoples R China.
   Tang, Sha, Chinese Acad Agr Sci, Inst Crop Sci, Beijing 100081, Peoples R China.}},
DOI = {{10.3390/ijms160920468}},
ISSN = {{1422-0067}},
Keywords = {{reference genes; salt stress; normalization; reverse
   transcription-quantitative PCR; Populus euphratica}},
Keywords-Plus = {{REAL-TIME PCR; POLYMERASE-CHAIN-REACTION; RELIABLE REFERENCE GENES;
   POPULUS-EUPHRATICA; RT-PCR; HOUSEKEEPING GENES; EXPRESSION ANALYSIS;
   SALT STRESS; SALINITY TOLERANCE; ABIOTIC STRESSES}},
Research-Areas = {{Biochemistry \& Molecular Biology; Chemistry}},
Web-of-Science-Categories  = {{Biochemistry \& Molecular Biology; Chemistry, Multidisciplinary}},
Author-Email = {{whling@bjfu.edu.cn
   whling@bjfu.edu.cn
   tangsha@caas.cn
   yuanchao@bjfu.edu.cn
   tqqetqq@bjfu.edu.cn
   yanyansu@bjfu.edu.cn
   hg\_li@bjfu.edu.cn
   lynnzhao@bjfu.edu.cn
   yinwl@bjfu.edu.cn
   ruizhao@bjfu.edu.cn
   xiaxl@bjfu.edu.cn}},
Funding-Acknowledgement = {{Hi-Tech Research and Development Program of China {[}2013AA102701];
   Fundamental Research Funds for the Central Universities {[}BLYJ201505];
   National Natural Science Foundation of China {[}31270656]; Joint
   Programs of the Scientific Research and Graduate Training from BMEC
   (Stress Resistance Mechanism of Poplar); Beijing Forestry University
   {[}B13007]; Program for Changjiang Scholars and Innovative Research Team
   in University {[}IRT13047]}},
Funding-Text = {{This work was supported by the Hi-Tech Research and Development Program
   of China (2013AA102701), the Fundamental Research Funds for the Central
   Universities (No. BLYJ201505), the National Natural Science Foundation
   of China (31270656), Joint Programs of the Scientific Research and
   Graduate Training from BMEC (Stress Resistance Mechanism of Poplar), 111
   Project of Beijing Forestry University (B13007), and Program for
   Changjiang Scholars and Innovative Research Team in University
   (IRT13047).}},
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Number-of-Cited-References = {{76}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{12}},
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Journal-ISO = {{Int. J. Mol. Sci.}},
Doc-Delivery-Number = {{CV8MD}},
Unique-ID = {{ISI:000364541000024}},
}

@article{ ISI:000361756900010,
Author = {Bandyopadhyay, Sanghamitra and Ray, Sumanta and Mukhopadhyay, Anirban
   and Maulik, Ujjwal},
Title = {{A review of in silico approaches for analysis and prediction of
   HIV-1-human protein-protein interactions}},
Journal = {{BRIEFINGS IN BIOINFORMATICS}},
Year = {{2015}},
Volume = {{16}},
Number = {{5}},
Pages = {{830-851}},
Month = {{SEP}},
Abstract = {{The computational or in silico approaches for analysing the HIV-1-human
   protein-protein interaction (PPI) network, predicting different host
   cellular factors and PPIs and discovering several pathways are gaining
   popularity in the field of HIV research. Although there exist quite a
   few studies in this regard, no previous effort has been made to review
   these works in a comprehensive manner. Here we review the computational
   approaches that are devoted to the analysis and prediction of
   HIV-1-human PPIs. We have broadly categorized these studies into two
   fields: computational analysis of HIV-1-human PPI network and prediction
   of novel PPIs. We have also presented a comparative assessment of these
   studies and proposed some methodologies for discussing the implication
   of their results. We have also reviewed different computational
   techniques for predicting HIV-1-human PPIs and provided a comparative
   study of their applicability. We believe that our effort will provide
   helpful insights to the HIV research community.}},
Publisher = {{OXFORD UNIV PRESS}},
Address = {{GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND}},
Type = {{Review}},
Language = {{English}},
Affiliation = {{Bandyopadhyay, S (Reprint Author), Indian Stat Inst, Machine Intelligence Unit, Dept Informat, Kolkata, India.
   Bandyopadhyay, Sanghamitra, Indian Stat Inst, Comp Sci, Kolkata, India.
   Ray, Sumanta, Jadavpur Univ, Dept Comp Sci \& Engn, Kolkata, India.
   Ray, Sumanta, Aliah Univ, Kolkata, India.
   Mukhopadhyay, Anirban, Univ Kalyani, Dept Comp Sci \& Engn, Comp Sci, Kalyani, W Bengal, India.
   Maulik, Ujjwal, Jadavpur Univ, Dept Comp Sci \& Engn, Comp Sci, Kolkata, India.}},
DOI = {{10.1093/bib/bbu041}},
ISSN = {{1467-5463}},
EISSN = {{1477-4054}},
Keywords = {{HIV-1-human PPI Network; computational PPI prediction; HIV dependency
   factor; association rule mining; biclustering; random forest classifier;
   semi supervised classification; rank aggregation; topological properties
   of network}},
Keywords-Plus = {{IMMUNODEFICIENCY-VIRUS TYPE-1; NETWORK MOTIFS; HIV-1 REPLICATION;
   STRUCTURAL SIMILARITY; BICLUSTERING APPROACH; CLOSED ITEMSETS;
   HUMAN-DISEASE; DATABASE; INFORMATION; RESOURCE}},
Research-Areas = {{Biochemistry \& Molecular Biology; Mathematical \& Computational Biology}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Mathematical \& Computational Biology}},
Author-Email = {{sanghami@isical.ac.in}},
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Number-of-Cited-References = {{93}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Brief. Bioinform.}},
Doc-Delivery-Number = {{CS0NF}},
Unique-ID = {{ISI:000361756900010}},
}

@article{ ISI:000360070500001,
Author = {Moreira, Catarina and Calado, Pavel and Martins, Bruno},
Title = {{Learning to rank academic experts in the DBLP dataset}},
Journal = {{EXPERT SYSTEMS}},
Year = {{2015}},
Volume = {{32}},
Number = {{4}},
Pages = {{477-493}},
Month = {{AUG}},
Abstract = {{Expert finding is an information retrieval task that is concerned with
   the search for the most knowledgeable people with respect to a specific
   topic, and the search is based on documents that describe people's
   activities. The task involves taking a user query as input and returning
   a list of people who are sorted by their level of expertise with respect
   to the user query. Despite recent interest in the area, the current
   state-of-the-art techniques lack in principled approaches for optimally
   combining different sources of evidence. This article proposes two
   frameworks for combining multiple estimators of expertise. These
   estimators are derived from textual contents, from graph-structure of
   the citation patterns for the community of experts and from profile
   information about the experts. More specifically, this article explores
   the use of supervised learning to rank methods, as well as rank
   aggregation approaches, for combining all of the estimators of
   expertise. Several supervised learning algorithms, which are
   representative of the pointwise, pairwise and listwise approaches, were
   tested, and various state-of-the-art data fusion techniques were also
   explored for the rank aggregation framework. Experiments that were
   performed on a dataset of academic publications from the Computer
   Science domain attest the adequacy of the proposed approaches.}},
Publisher = {{WILEY-BLACKWELL}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Moreira, C (Reprint Author), Inst Super Tecn, INESC ID, Ave Prof Cavaco Silva, P-2744016 Porto Salvo, Portugal.
   Moreira, Catarina; Calado, Pavel; Martins, Bruno, Inst Super Tecn, INESC ID, P-2744016 Porto Salvo, Portugal.}},
DOI = {{10.1111/exsy.12062}},
ISSN = {{0266-4720}},
EISSN = {{1468-0394}},
Keywords = {{Learning to Rank; Rank Aggregation; Expert Finding; Information
   Retrieval; Data Fusion}},
Keywords-Plus = {{ALGORITHMS; NETWORKS; INDEX}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Computer Science, Theory \&
   Methods}},
Author-Email = {{catarina.p.moreira@ist.utl.pt}},
ResearcherID-Numbers = {{Calado, Pavel/M-8535-2013}},
ORCID-Numbers = {{Calado, Pavel/0000-0001-6478-229X}},
Funding-Acknowledgement = {{Fundacao para a Ciencia e Tecnologia (FCT) through INESC-ID
   {[}PEst-OE/EEI/LA0021/2013]; FCT {[}PTDC/EIA-EIA/115346/2009]}},
Funding-Text = {{This work was supported by Fundacao para a Ciencia e Tecnologia (FCT)
   through INESC-ID multi annual funding under project
   PEst-OE/EEI/LA0021/2013 and through FCT Project SMARTIS (ref.
   PTDC/EIA-EIA/115346/2009).}},
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Number-of-Cited-References = {{55}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{7}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{Expert Syst.}},
Doc-Delivery-Number = {{CP7LW}},
Unique-ID = {{ISI:000360070500001}},
}

@article{ ISI:000354391500016,
Author = {Wang, Baoli and Liang, Jiye and Qian, Yuhua},
Title = {{Determining decision makers' weights in group ranking: a granular
   computing method}},
Journal = {{INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS}},
Year = {{2015}},
Volume = {{6}},
Number = {{3}},
Pages = {{511-521}},
Month = {{JUN}},
Abstract = {{Deriving the consensus ranking(s) from a set of rankings plays an
   important role in group decision making. However, the relative
   importance, i.e. weight of a decision maker, is ignored in most of the
   ordinal ranking methods. This paper aims to determine the weights of
   decision makers by measuring the support degree of each pair of ordinal
   rankings. We first define the similarity degree of dominance granular
   structures to depict the mutual relations of the ordinal rankings. Then,
   the support degree, which is obtained from similarity degree, is
   presented to determine weights of decision makers. Finally, an improved
   programming model is proposed to compute the consensus rankings by
   minimizing the violation with the weighted ranking(s). Two examples are
   given to illustrate the rationality of the proposed model.}},
Publisher = {{SPRINGER HEIDELBERG}},
Address = {{TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Liang, JY (Reprint Author), Shanxi Univ, Sch Comp \& Informat Technol, Minist Educ, Key Lab Computat Intelligence \& Chinese Informat, Taiyuan 044000, Shanxi, Peoples R China.
   Wang, Baoli; Liang, Jiye; Qian, Yuhua, Shanxi Univ, Sch Comp \& Informat Technol, Minist Educ, Key Lab Computat Intelligence \& Chinese Informat, Taiyuan 044000, Shanxi, Peoples R China.
   Wang, Baoli, Yuncheng Univ, Dept Appl Math, Yuncheng 044000, Shanxi, Peoples R China.
   Liang, Jiye, Taiyuan Normal Univ, Dept Comp Sci \& Technol, Taiyuan 030012, Shanxi, Peoples R China.}},
DOI = {{10.1007/s13042-014-0278-5}},
ISSN = {{1868-8071}},
EISSN = {{1868-808X}},
Keywords = {{Total ranking; Partial ranking; Similarity degree; Support degree;
   Granular computing}},
Keywords-Plus = {{ROUGH SET-THEORY; KNOWLEDGE GRANULATION; LINGUISTIC INFORMATION;
   PREFERENCE STRUCTURES; COLLECTIVE PREORDER; DISTANCE; ENTROPY;
   UNCERTAINTY; OPERATOR; MEMBERS}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{pollycomputer@163.com
   ljy@sxu.edu.cn
   jinchengqyh@126.com}},
Funding-Acknowledgement = {{National Natural Science Foundation of China {[}71031006]; Shanxi
   Provincial Foundation for Returned Scholars {[}2013-101]; Construction
   Project of the Science and Technology Basic Condition Platform of Shanxi
   Province {[}2012091002-0101]; Research Projects in Education Teaching of
   Yuncheng University {[}JY2011025]}},
Funding-Text = {{This work was supported by the National Natural Science Foundation of
   China (No. 71031006), the Shanxi Provincial Foundation for Returned
   Scholars (No. 2013-101), the Construction Project of the Science and
   Technology Basic Condition Platform of Shanxi Province (No.
   2012091002-0101) and the Research Projects in Education Teaching of
   Yuncheng University (No. JY2011025).}},
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Number-of-Cited-References = {{48}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{13}},
Usage-Count-Since-2013 = {{19}},
Journal-ISO = {{Int. J. Mach. Learn. Cybern.}},
Doc-Delivery-Number = {{CH9YB}},
Unique-ID = {{ISI:000354391500016}},
}

@article{ ISI:000354476600010,
Author = {Ozdemiray, Ahmet Murat and Altingovde, Ismail Sengor},
Title = {{Explicit Search Result Diversification Using Score and Rank Aggregation
   Methods}},
Journal = {{JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY}},
Year = {{2015}},
Volume = {{66}},
Number = {{6}},
Pages = {{1212-1228}},
Month = {{JUN}},
Abstract = {{Search result diversification is one of the key techniques to cope with
   the ambiguous and underspecified information needs of web users. In the
   last few years, strategies that are based on the explicit knowledge of
   query aspects emerged as highly effective ways of diversifying search
   results. Our contributions in this article are two-fold. First, we
   extensively evaluate the performance of a state-of-the-art explicit
   diversification strategy and pin-point its potential weaknesses. We
   propose basic yet novel optimizations to remedy these weaknesses and
   boost the performance of this algorithm. As a second contribution,
   inspired by the success of the current diversification strategies that
   exploit the relevance of the candidate documents to individual query
   aspects, we cast the diversification problem into the problem of ranking
   aggregation. To this end, we propose to materialize the re-rankings of
   the candidate documents for each query aspect and then merge these
   rankings by adapting the score(-based) and rank(-based) aggregation
   methods. Our extensive experimental evaluations show that certain
   ranking aggregation methods are superior to existing explicit
   diversification strategies in terms of diversification effectiveness.
   Furthermore, these ranking aggregation methods have lower computational
   complexity than the state-of-the-art diversification strategies.}},
Publisher = {{WILEY-BLACKWELL}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ozdemiray, AM (Reprint Author), Middle E Tech Univ, Dept Comp Engn, TR-06531 Ankara, Turkey.
   Ozdemiray, Ahmet Murat; Altingovde, Ismail Sengor, Middle E Tech Univ, Dept Comp Engn, TR-06531 Ankara, Turkey.}},
DOI = {{10.1002/asi.23259}},
ISSN = {{2330-1635}},
EISSN = {{2330-1643}},
Keywords = {{search engines; information storage and retrieval systems; meta search
   engines}},
Keywords-Plus = {{INFORMATION-RETRIEVAL; NORMALIZATION; METASEARCH; FRAMEWORK}},
Research-Areas = {{Computer Science; Information Science \& Library Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Information Science \& Library
   Science}},
Author-Email = {{murat.ozdemiray@tubitak.gov.tr
   altingovde@ceng.metu.edu.tr}},
Funding-Acknowledgement = {{Scientific and Technological Research Council of Turkey (TUBTAK)
   {[}113E065]; METU {[}BAP-08-11-2013-055]}},
Funding-Text = {{This work is partially funded by The Scientific and Technological
   Research Council of Turkey (TUBTAK) under the grant no. 113E065 and METU
   BAP-08-11-2013-055. I.S. Altingovde acknowledges the Yahoo! Faculty
   Research and Engagement Program.}},
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Number-of-Cited-References = {{52}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{12}},
Usage-Count-Since-2013 = {{16}},
Doc-Delivery-Number = {{CI1BY}},
Unique-ID = {{ISI:000354476600010}},
}

@article{ ISI:000355226800001,
Author = {Tang, Kun and Xu, Hua},
Title = {{Prognostic value of meta-signature miRNAs in renal cell carcinoma: an
   integrated miRNA expression profiling analysis}},
Journal = {{SCIENTIFIC REPORTS}},
Year = {{2015}},
Volume = {{5}},
Month = {{MAY 14}},
Abstract = {{To identify a robust panel of microRNA (miRNA) signatures that can
   distinguish renal cell carcinoma (RCC) from normal kidney using miRNA
   expression levels. We performed a comprehensive metaanalysis of 29
   published studies that compared the miRNA expression profiles of RCC
   tissues and adjacent normal tissues (NT) to determine candidate miRNAs
   as prognostic biomarkers for RCC. Using vote-counting strategy and
   robust rank aggregation method, we identified a statistically
   significant miRNA meta-signature of two upregulated (miR-21, miR-210)
   and three downregulated (miR-141, miR-200c and miR-429) miRNAs. X-tile
   plot was used to generate the optimum cut-off point for the 15 different
   deregulated miRNAs and Kaplan-Meier method was used to calculate CSS. In
   a cohort of 45 patients, the high expression of miR-21 (HR: 5.46,
   95\%CI: 2.02-53.39) and miR-210 (HR: 6.85, 95\%CI: 2.13-43.36), the low
   expression of miR-141 (HR: 0.16, 95\%CI: 0.004-0.18), miR-200c (HR:
   0.08, 95\%CI: 0.01-0.43) and miR-429 (HR: 0.18, 95\%CI: 0.02-0.50) were
   associated with poor cancer-specific survival (CSS) following RCC
   resection. We also constructed a five-miRNAs-based classifier as a
   reliable prognostic and predictive tool for CSS in patients with RCC,
   especially in clear cell RCC (ccRCC) (HR: 5.46, 95\% CI: 1.51-19.66).
   This method might facilitate patient counselling and individualise
   management of RCC.}},
Publisher = {{NATURE PUBLISHING GROUP}},
Address = {{MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Xu, H (Reprint Author), Huazhong Univ Sci \& Technol, Tongji Med Coll, Tongji Hosp, Dept Urol, Wuhan 430074, Peoples R China.
   Tang, Kun; Xu, Hua, Huazhong Univ Sci \& Technol, Tongji Med Coll, Tongji Hosp, Dept Urol, Wuhan 430074, Peoples R China.
   Tang, Kun; Xu, Hua, Huazhong Univ Sci \& Technol, Tongji Med Coll, Tongji Hosp, Inst Urol, Wuhan 430074, Peoples R China.}},
DOI = {{10.1038/srep10272}},
Article-Number = {{10272}},
ISSN = {{2045-2322}},
Keywords-Plus = {{MICRORNA EXPRESSION; FUNCTIONAL-SIGNIFICANCE; GENE-EXPRESSION; CANCER;
   MIGRATION; IDENTIFICATION; METAANALYSIS; METASTASIS; INVASION; MARKER}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{xuhuawhu@163.com}},
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Number-of-Cited-References = {{50}},
Times-Cited = {{6}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Sci Rep}},
Doc-Delivery-Number = {{CJ1FD}},
Unique-ID = {{ISI:000355226800001}},
}

@article{ ISI:000352995000010,
Author = {Taba, Seyedamir Tavakoli and Hossain, Liaquat and Atkinson, Simon Reay
   and Lewis, Sarah},
Title = {{Towards understanding longitudinal collaboration networks: a case of
   mammography performance research}},
Journal = {{SCIENTOMETRICS}},
Year = {{2015}},
Volume = {{103}},
Number = {{2}},
Pages = {{531-544}},
Month = {{MAY}},
Abstract = {{In this paper, we explore the longitudinal research collaboration
   network of `mammography performance' over 30 years by creating and
   analysing a large collaboration network data using Scopus. The study of
   social networks using longitudinal data may provide new insights into
   how this collaborative research evolve over time as well as what type of
   actors influence the whole network in time. The methods and findings
   presented in this work aim to assist identifying key actors in other
   research collaboration networks. In doing so, we apply a rank
   aggregation technique to centrality measures in order to derive a single
   ranking of influential actors. We argue that there is a strong
   correlation between the level of degree and closeness centralities of an
   actor and its influence in the research collaboration network (at
   macro/country level).}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Hossain, L (Reprint Author), Univ Hong Kong, Div Informat \& Technol Studies, Fac Educ, Runme Shaw Bldg, Pokfulam, Hong Kong, Peoples R China.
   Taba, Seyedamir Tavakoli; Hossain, Liaquat; Atkinson, Simon Reay, Univ Sydney, Complex Syst Res Grp, Sch Civil Engn, Fac Engn \& IT, Sydney, NSW 2006, Australia.
   Hossain, Liaquat, Univ Hong Kong, Div Informat \& Technol Studies, Fac Educ, Pokfulam, Hong Kong, Peoples R China.
   Lewis, Sarah, Univ Sydney, Med Imaging Optimisat \& Percept Grp MIOPeG, Fac Hlth Sci, Brain Mind Res Inst, Sydney, NSW 2141, Australia.}},
DOI = {{10.1007/s11192-015-1560-3}},
ISSN = {{0138-9130}},
EISSN = {{1588-2861}},
Keywords = {{Research collaboration network; Mammography performance; Social network
   analysis; Longitudinal data; Influential actors}},
Keywords-Plus = {{SCIENTIFIC COLLABORATION; SOCIAL NETWORKS; SELF-ORGANIZATION;
   CENTRALITY; BETWEENNESS; EVOLUTION; GROWTH; DESIGN; TRADE}},
Research-Areas = {{Computer Science; Information Science \& Library Science}},
Web-of-Science-Categories  = {{Computer Science, Interdisciplinary Applications; Information Science \&
   Library Science}},
Author-Email = {{amir.tavakoli@sydney.edu.au
   lhossain@hku.hk
   simon.reayatkinson@sydney.edu.au
   sarah.lewis@sydney.edu.au}},
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Number-of-Cited-References = {{40}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{14}},
Usage-Count-Since-2013 = {{27}},
Journal-ISO = {{Scientometrics}},
Doc-Delivery-Number = {{CG0WW}},
Unique-ID = {{ISI:000352995000010}},
}

@article{ ISI:000351778300003,
Author = {Kalivas, John H. and Heberger, Karoly and Andries, Erik},
Title = {{Sum of ranking differences (SRD) to ensemble multivariate calibration
   model merits for tuning parameter selection and comparing calibration
   methods}},
Journal = {{ANALYTICA CHIMICA ACTA}},
Year = {{2015}},
Volume = {{869}},
Pages = {{21-33}},
Month = {{APR 15}},
Abstract = {{Most multivariate calibration methods require selection of tuning
   parameters, such as partial least squares (PLS) or the Tikhonov
   regularization variant ridge regression (RR). Tuning parameter values
   determine the direction and magnitude of respective model vectors
   thereby setting the resultant predication abilities of the model
   vectors. Simultaneously, tuning parameter values establish the
   corresponding bias/variance and the underlying selectivity/sensitivity
   tradeoffs. Selection of the final tuning parameter is often accomplished
   through some form of cross-validation and the resultant root mean square
   error of cross-validation (RMSECV) values are evaluated. However,
   selection of a ``good{''} tuning parameter with this one model
   evaluation merit is almost impossible. Including additional model merits
   assists tuning parameter selection to provide better balanced models as
   well as allowing for a reasonable comparison between calibration
   methods. Using multiple merits requires decisions to be made on how to
   combine and weight the merits into an information criterion. An
   abundance of options are possible. Presented in this paper is the sum of
   ranking differences (SRD) to ensemble a collection of model evaluation
   merits varying across tuning parameters. It is shown that the SRD
   consensus ranking of model tuning parameters allows automatic selection
   of the final model, or a collection of models if so desired.
   Essentially, the user's preference for the degree of balance between
   bias and variance ultimately decides the merits used in SRD and hence,
   the tuning parameter values ranked lowest by SRD for automatic
   selection. The SRD process is also shown to allow simultaneous
   comparison of different calibration methods for a particular data set in
   conjunction with tuning parameter selection. Because SRD evaluates
   consistency across multiple merits, decisions on how to combine and
   weight merits are avoided. To demonstrate the utility of SRD, a near
   infrared spectral data set and a quantitative structure activity
   relationship (QSAR) data set are evaluated using PLS and RR. (C) 2015
   Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Kalivas, JH (Reprint Author), Idaho State Univ, Dept Chem, Pocatello, ID 83209 USA.
   Kalivas, John H., Idaho State Univ, Dept Chem, Pocatello, ID 83209 USA.
   Heberger, Karoly, Hungarian Acad Sci, Res Ctr Nat Sci, H-1025 Budapest, Hungary.
   Andries, Erik, Univ New Mexico, Ctr Adv Res Comp, Albuquerque, NM 87106 USA.
   Andries, Erik, Cent New Mexico Community Coll, Dept Math, Albuquerque, NM 87106 USA.}},
DOI = {{10.1016/j.aca.2014.12.056}},
ISSN = {{0003-2670}},
EISSN = {{1873-4324}},
Keywords = {{Sum of ranking differences; Multivariate calibration; Partial least
   squares; Ridge regression; Model comparison}},
Keywords-Plus = {{CROSS-VALIDATION; DATA FUSION; TRADE-OFF; REGRESSION; SIMILARITY;
   OPTIMIZATION; SPECTROSCOPY; PREDICTIONS; SENSITIVITY; COMBINATION}},
Research-Areas = {{Chemistry}},
Web-of-Science-Categories  = {{Chemistry, Analytical}},
Author-Email = {{kalijohn@isu.edu}},
Funding-Acknowledgement = {{National Science Foundation {[}CHE-1111053]; MPS Chemistry; OCI Venture
   Fund; OTKA {[}K112547]}},
Funding-Text = {{This material is based upon work supported by the National Science
   Foundation under Grant No. CHE-1111053 (co-funded by MPS Chemistry and
   the OCI Venture Fund) and is gratefully acknowledged by the authors.
   Karoly Heberger's contribution was supported by OTKA under Contract No.
   K112547.}},
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Number-of-Cited-References = {{62}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{8}},
Usage-Count-Since-2013 = {{18}},
Journal-ISO = {{Anal. Chim. Acta}},
Doc-Delivery-Number = {{CE4CL}},
Unique-ID = {{ISI:000351778300003}},
}

@article{ ISI:000352269500008,
Author = {Kim, Minji and Farnoud, Farzad and Milenkovic, Olgica},
Title = {{HyDRA: gene prioritization via hybrid distance-score rank aggregation}},
Journal = {{BIOINFORMATICS}},
Year = {{2015}},
Volume = {{31}},
Number = {{7}},
Pages = {{1034-1043}},
Month = {{APR 1}},
Abstract = {{A Summary: Gene prioritization refers to a family of computational
   techniques for inferring disease genes through a set of training genes
   and carefully chosen similarity criteria. Test genes are scored based on
   their average similarity to the training set, and the rankings of genes
   under various similarity criteria are aggregated via statistical
   methods. The contributions of our work are threefold: (i) first, based
   on the realization that there is no unique way to define an optimal
   aggregate for rankings, we investigate the predictive quality of a
   number of new aggregation methods and known fusion techniques from
   machine learning and social choice theory. Within this context, we
   quantify the influence of the number of training genes and similarity
   criteria on the diagnostic quality of the aggregate and perform in-depth
   cross-validation studies; (ii) second, we propose a new approach to
   genomic data aggregation, termed HyDRA (Hybrid Distance-score Rank
   Aggregation), which combines the advantages of score-based and
   combinatorial aggregation techniques. We also propose incorporating a
   new top-versus-bottom (TvB) weighting feature into the hybrid schemes.
   The TvB feature ensures that aggregates are more reliable at the top of
   the list, rather than at the bottom, since only top candidates are
   tested experimentally; (iii) third, we propose an iterative procedure
   for gene discovery that operates via successful augmentation of the set
   of training genes by genes discovered in previous rounds, checked for
   consistency.
   Motivation: Fundamental results from social choice theory, political and
   computer sciences, and statistics have shown that there exists no
   consistent, fair and unique way to aggregate rankings. Instead, one has
   to decide on an aggregation approach using predefined set of desirable
   properties for the aggregate. The aggregation methods fall into two
   categories, score-and distance-based approaches, each of which has its
   own drawbacks and advantages. This work is motivated by the observation
   that merging these two techniques in a computationally efficient manner,
   and by incorporating additional constraints, one can ensure that the
   predictive quality of the resulting aggregation algorithm is very high.
   Results: We tested HyDRA on a number of gene sets, including autism,
   breast cancer, colorectal cancer, endometriosis, ischaemic stroke,
   leukemia, lymphoma and osteoarthritis. Furthermore, we performed
   iterative gene discovery for glioblastoma, meningioma and breast cancer,
   using a sequentially augmented list of training genes related to the
   Turcot syndrome, Li-Fraumeni condition and other diseases. The methods
   outperform state-of-the-art software tools such as ToppGene and
   Endeavour. Despite this finding, we recommend as best practice to take
   the union of top-ranked items produced by different methods for the
   final aggregated list.}},
Publisher = {{OXFORD UNIV PRESS}},
Address = {{GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Kim, M (Reprint Author), Univ Illinois, Dept Elect \& Comp Engn, Urbana, IL 61801 USA.
   Kim, Minji; Farnoud, Farzad; Milenkovic, Olgica, Univ Illinois, Dept Elect \& Comp Engn, Urbana, IL 61801 USA.}},
DOI = {{10.1093/bioinformatics/btu766}},
ISSN = {{1367-4803}},
EISSN = {{1460-2059}},
Keywords-Plus = {{NETWORK-BASED PRIORITIZATION; CANDIDATE DISEASE GENES; DATA FUSION;
   ASSOCIATION; INTEGRATION; ALGORITHMS; SIMILARITY; PREDICTION; SERVER}},
Research-Areas = {{Biochemistry \& Molecular Biology; Biotechnology \& Applied
   Microbiology; Computer Science; Mathematical \& Computational Biology;
   Mathematics}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Biotechnology \& Applied Microbiology;
   Computer Science, Interdisciplinary Applications; Mathematical \&
   Computational Biology; Statistics \& Probability}},
Author-Email = {{mkim158@illinois.edu}},
Funding-Acknowledgement = {{National Science Foundation (NSF) {[}CCF 0809895, CCF 1218764, CSoI-CCF
   0939370, IOS 1339388]}},
Funding-Text = {{The work was supported in part by the National Science Foundation (NSF)
   under grants CCF 0809895, CCF 1218764, CSoI-CCF 0939370, and IOS
   1339388.}},
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Number-of-Cited-References = {{37}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{9}},
Journal-ISO = {{Bioinformatics}},
Doc-Delivery-Number = {{CF0YC}},
Unique-ID = {{ISI:000352269500008}},
}

@article{ ISI:000351310600007,
Author = {Ali, Rashid and Naim, Iram},
Title = {{User feedback based metasearching using neural network}},
Journal = {{INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS}},
Year = {{2015}},
Volume = {{6}},
Number = {{2}},
Pages = {{265-275}},
Month = {{APR}},
Abstract = {{Metasearch engines are the web services that receive user queries and
   dispatch them to multiple crawler based search engines. After this, they
   collect the returned search results, reorder them and present the
   reordered list to the end user. To combine the results from different
   search engines, a metasearch engine may use different rank aggregation
   techniques to aggregate the various rankings of the search results to
   generate an overall ranking. If different rank aggregation techniques
   are used to collate search results, the results of metasearching for the
   same query may vary for the same set of participating search engines. In
   this paper, we discuss a metasearching technique that utilizes neural
   network based rank aggregation. Here, we formulate the rank aggregation
   problem as a function approximation problem. As the multilayer
   perceptrons are considered universal approximators, we use a multilayer
   perceptron for rank aggregation. We compare the performance of the
   neural network based method with four other methods namely rough set
   based method, modified rough set based method, Borda's method and a
   Markov Chain based method (MC2) using three independent evaluators.
   Experimentally, we find that the neural network based method performs
   better than each of these four methods.}},
Publisher = {{SPRINGER HEIDELBERG}},
Address = {{TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ali, R (Reprint Author), Taif Univ, Coll Comp \& Informat Technol, At Taif, Saudi Arabia.
   Ali, Rashid, Taif Univ, Coll Comp \& Informat Technol, At Taif, Saudi Arabia.
   Naim, Iram, MJP Rohilkhand Univ, Dept Comp Engn \& Informat Technol, Bareilly, Uttar Pradesh, India.}},
DOI = {{10.1007/s13042-013-0212-2}},
ISSN = {{1868-8071}},
EISSN = {{1868-808X}},
Keywords = {{Metasearching; User feedback; Neural network; Correlation coefficient;
   Performance evaluation}},
Keywords-Plus = {{WEB; PREDICTION; ALGORITHM}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{rashidaliamu@rediffmail.com
   iram.naim03cs@gmail.com}},
Cited-References = {{Ahmad N., 2002, P INT C KNOWL BAS CO, P193.
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Number-of-Cited-References = {{38}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Int. J. Mach. Learn. Cybern.}},
Doc-Delivery-Number = {{CD7YB}},
Unique-ID = {{ISI:000351310600007}},
}

@article{ ISI:000351987300014,
Author = {Saint-Marcoux, Denis and Proust, Helene and Dolan, Liam and Langdale,
   Jane A.},
Title = {{Identification of Reference Genes for Real-Time Quantitative PCR
   Experiments in the Liverwort Marchantia polymorpha}},
Journal = {{PLOS ONE}},
Year = {{2015}},
Volume = {{10}},
Number = {{3}},
Month = {{MAR 23}},
Abstract = {{Real-time quantitative polymerase chain reaction (qPCR) has become
   widely used as a method to compare gene transcript levels across
   different conditions. However, selection of suitable reference genes to
   normalize qPCR data is required for accurate transcript level analysis.
   Recently, Marchantia polymorpha has been adopted as a model for the
   study of liverwort development and land plant evolution. Identification
   of appropriate reference genes has therefore become a necessity for gene
   expression studies. In this study, transcript levels of eleven candidate
   reference genes have been analyzed across a range of biological contexts
   that encompass abiotic stress, hormone treatment and different
   developmental stages. The consistency of transcript levels was assessed
   using both geNorm and NormFinder algorithms, and a consensus ranking of
   the different candidate genes was then obtained. MpAPT and MpACT showed
   relatively constant transcript levels across all conditions tested
   whereas the transcript levels of other candidate genes were clearly
   influenced by experimental conditions. By analyzing transcript levels of
   phosphate and nitrate starvation reporter genes, we confirmed that MpAPT
   and MpACT are suitable reference genes in M. polymorpha and also
   demonstrated that normalization with an inappropriate gene can lead to
   erroneous analysis of qPCR data.}},
Publisher = {{PUBLIC LIBRARY SCIENCE}},
Address = {{1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Proust, H (Reprint Author), Univ Oxford, Dept Plant Sci, Oxford, England.
   Saint-Marcoux, Denis; Proust, Helene; Dolan, Liam; Langdale, Jane A., Univ Oxford, Dept Plant Sci, Oxford, England.}},
DOI = {{10.1371/journal.pone.0118678}},
Article-Number = {{e0118678}},
ISSN = {{1932-6203}},
Keywords-Plus = {{AGROBACTERIUM-MEDIATED TRANSFORMATION; CANDIDATE REFERENCE GENES; LAND
   PLANTS; EXPRESSION ANALYSIS; STRESS CONDITIONS; ABIOTIC STRESSES;
   BRASSICA-NAPUS; NORMALIZATION; ARABIDOPSIS; VALIDATION}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{helene.proust@plants.ox.ac.uk}},
Funding-Acknowledgement = {{ERC {[}EVO500]}},
Funding-Text = {{This work was funded by ERC Advanced Investigator grants to JAL (EDIP)
   and LD (EVO500). The funders had no role in study design, data
   collection and analysis, decision to publish, or preparation of the
   manuscript.}},
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Number-of-Cited-References = {{39}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{8}},
Usage-Count-Since-2013 = {{12}},
Journal-ISO = {{PLoS One}},
Doc-Delivery-Number = {{CE6ZS}},
Unique-ID = {{ISI:000351987300014}},
}

@article{ ISI:000351320100007,
Author = {Liang, Shangsong and de Rijke, Maarten},
Title = {{Burst-aware data fusion for microblog search}},
Journal = {{INFORMATION PROCESSING \& MANAGEMENT}},
Year = {{2015}},
Volume = {{51}},
Number = {{2, SI}},
Pages = {{89-113}},
Month = {{MAR}},
Abstract = {{We consider the problem of searching posts in microblog environments. We
   frame this microblog post search problem as a late data fusion problem.
   Previous work on data fusion has mainly focused on aggregating document
   lists based on retrieval status values or ranks of documents without
   fully utilizing temporal features of the set of documents being fused.
   Additionally, previous work on data fusion has often worked on the
   assumption that only documents that are highly ranked in many of the
   lists are likely to be of relevance. We propose BurstFuseX, a fusion
   model that not only utilizes a microblog post's ranking information but
   also exploits its publication time. BurstFuseX builds on an existing
   fusion method and rewards posts that are published in or near a burst of
   posts that are highly ranked in many of the lists being aggregated. We
   experimentally verify the effectiveness of the proposed late data fusion
   algorithm, and demonstrate that in terms of mean average precision it
   significantly outperforms the standard, state-of-the-art fusion
   approaches as well as burst or time-sensitive retrieval methods. (C)
   2014 Elsevier Ltd. All rights reserved.}},
Publisher = {{ELSEVIER SCI LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Liang, SS (Reprint Author), Univ Amsterdam, Sci Pk 904, NL-1098 XH Amsterdam, Netherlands.
   Liang, Shangsong; de Rijke, Maarten, Univ Amsterdam, NL-1098 XH Amsterdam, Netherlands.}},
DOI = {{10.1016/j.ipm.2014.10.008}},
ISSN = {{0306-4573}},
EISSN = {{1873-5371}},
Keywords = {{Information retrieval; Microblog search; Rank aggregation; Burst
   detection; Temporal information retrieval}},
Keywords-Plus = {{RETRIEVAL; INFORMATION}},
Research-Areas = {{Computer Science; Information Science \& Library Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Information Science \& Library
   Science}},
Author-Email = {{s.liang@uva.nl
   derijke@uva.nl}},
Funding-Acknowledgement = {{China Scholarship Council; European Community {[}288024, 312827];
   Netherlands Organisation for Scientific Research (NWO) {[}727.011.005,
   612.001.116, HOR-11-10, 640.006.013]; Center for Creation, Content and
   Technology (CCCT); QuaMerdes project - CLARIN-nl program; TROVe project
   - CLARIAH program; Dutch national program COMMIT; ESF Research Network
   Program ELIAS; Elite Network Shifts project - Royal Dutch Academy of
   Sciences (KNAW); Netherlands eScience Center {[}027.012.105]; Yahoo!
   Faculty Research and Engagement Program; Microsoft Research PhD program;
   HPC Fund}},
Funding-Text = {{This research was partially supported by the China Scholarship Council,
   the European Community's Seventh Framework Programme (FP7/2007-2013)
   under grant agreements nr 288024 (LiMoSINe) and nr 312827 (VOX-Pol), the
   Netherlands Organisation for Scientific Research (NWO) under project nrs
   727.011.005, 612.001.116, HOR-11-10, 640.006.013, the Center for
   Creation, Content and Technology (CCCT), the QuaMerdes project funded by
   the CLARIN-nl program, the TROVe project funded by the CLARIAH program,
   the Dutch national program COMMIT, the ESF Research Network Program
   ELIAS, the Elite Network Shifts project funded by the Royal Dutch
   Academy of Sciences (KNAW), the Netherlands eScience Center under
   project number 027.012.105 the Yahoo! Faculty Research and Engagement
   Program, the Microsoft Research PhD program, and the HPC Fund.}},
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Number-of-Cited-References = {{91}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{8}},
Usage-Count-Since-2013 = {{14}},
Journal-ISO = {{Inf. Process. Manage.}},
Doc-Delivery-Number = {{CD8BL}},
Unique-ID = {{ISI:000351320100007}},
}

@article{ ISI:000351557200003,
Author = {Pujari, Manisha and Kanawati, Rushed},
Title = {{LINK PREDICTION IN MULTIPLEX NETWORKS}},
Journal = {{NETWORKS AND HETEROGENEOUS MEDIA}},
Year = {{2015}},
Volume = {{10}},
Number = {{1, SI}},
Pages = {{17-35}},
Month = {{MAR}},
Abstract = {{In this work we present a new approach for co-authorship link prediction
   based on leveraging information contained in general bibliographical
   multiplex networks. A multiplex network is a graph defined over a set of
   nodes linked by different types of relations. For instance, the
   multiplex network we are studying here is defined as follows : nodes
   represent authors and links can be one of the following types:
   co-authorship links, co-venue attending links and co-citing links. A
   supervised-machine learning based link prediction approach is applied. A
   link formation model is learned based on a set of topological attributes
   describing both positive and negative examples. While such an approach
   has been successfully applied in the context on simple networks,
   different options can be applied to extend it to multiplex networks. One
   option is to compute topological attributes in each layer of the
   multiplex. Another one is to compute directly new multiplex-based
   attributes quantifying the multiplex nature of dyads (potential links).
   These different approaches are studied and compared through experiments
   on real datasets extracted from the bibliographical database DBLP.}},
Publisher = {{AMER INST MATHEMATICAL SCIENCES}},
Address = {{PO BOX 2604, SPRINGFIELD, MO 65801-2604 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Pujari, M (Reprint Author), Univ Paris 13, SPC, LIPN, CNRS UMR 7030, 99 Ave JB Clement, F-93430 Villetaneuse, France.
   Pujari, Manisha; Kanawati, Rushed, Univ Paris 13, SPC, LIPN, CNRS UMR 7030, F-93430 Villetaneuse, France.}},
DOI = {{10.3934/nhm.2015.10.17}},
ISSN = {{1556-1801}},
EISSN = {{1556-181X}},
Keywords = {{Complex network analysis; multiplex network; link prediction; rank
   aggregation; bibliographical networks}},
Keywords-Plus = {{SOCIAL NETWORKS; RECOMMENDATION}},
Research-Areas = {{Mathematics}},
Web-of-Science-Categories  = {{Mathematics, Interdisciplinary Applications}},
Author-Email = {{manisha.pujari@lipn.univ-paris13.fr
   rushed.kanawati@lipn.univ-paris13.fr}},
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Number-of-Cited-References = {{45}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{6}},
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Journal-ISO = {{Netw. Heterog. Media}},
Doc-Delivery-Number = {{CE1FJ}},
Unique-ID = {{ISI:000351557200003}},
}

@article{ ISI:000349843000008,
Author = {Serafin, Alice and Foco, Luisa and Zanigni, Stefano and Blankenburg,
   Hagen and Picard, Anne and Zanon, Alessandra and Giannini, Giulia and
   Pichler, Irene and Facheris, Maurizio F. and Cortelli, Pietro and
   Pramstaller, Peter P. and Hicks, Andrew A. and Domingues, Francisco S.
   and Schwienbacher, Christine},
Title = {{Overexpression of blood microRNAs 103a, 30b, and 29a in L-dopa-treated
   patients with PD}},
Journal = {{NEUROLOGY}},
Year = {{2015}},
Volume = {{84}},
Number = {{7}},
Pages = {{645-653}},
Month = {{FEB 17}},
Abstract = {{Objective:The aims of the present study were to profile the expression
   of several candidate microRNAs (miRNAs) in blood from l-dopa-treated and
   drug-naive patients with Parkinson disease (PD) vs unaffected controls
   and to interpret the miRNA expression data in a biological
   context.Methods:We analyzed RNAs from peripheral blood of 36
   l-dopa-treated, 10 drug-naive patients with PD and unaffected controls
   matched 1:1 by sex and age. We evaluated expression by reverse
   transcription-quantitative real-time PCR, and we analyzed data using a
   2-tailed paired t test. To detect miRNA targets, several miRNA resources
   were combined to generate an overall score for each candidate gene using
   weighted rank aggregation.Results:Significant overexpression of
   miR-103a-3p (p < 0.0001), miR-30b-5p (p = 0.002), and miR-29a-3p (p =
   0.005) in treated patients with PD was observed, and promising candidate
   target genes for these were revealed by an integrated in silico
   analysis.Conclusions:We revealed 3 candidate biomarkers for PD. miRNAs
   30b-5p and 29a-3p replicated a documented deregulation in PD albeit
   opposite to published data, while for miR-103a-3p, we demonstrated for
   the first time an overexpression in treated patients with PD. Expression
   studies in patients and/or in isolated peripheral blood mononuclear
   cells before and after l-dopa administration are necessary to define the
   involvement of l-dopa treatment in the observed overexpression. Our in
   silico analysis to prioritize targets of deregulated miRNAs identified
   candidate target genes, including genes related to neurodegeneration and
   PD. Despite the preliminary character of our study, the results provide
   a rationale for further clarifying the role of the identified miRNAs in
   the pathogenesis of PD and for validating their diagnostic potential.}},
Publisher = {{LIPPINCOTT WILLIAMS \& WILKINS}},
Address = {{TWO COMMERCE SQ, 2001 MARKET ST, PHILADELPHIA, PA 19103 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Schwienbacher, C (Reprint Author), European Acad Bozen Bolzano EURAC, Ctr Biomed, Bolzano, Italy.
   Serafin, Alice; Foco, Luisa; Zanigni, Stefano; Blankenburg, Hagen; Picard, Anne; Zanon, Alessandra; Giannini, Giulia; Pichler, Irene; Facheris, Maurizio F.; Pramstaller, Peter P.; Hicks, Andrew A.; Domingues, Francisco S.; Schwienbacher, Christine, European Acad Bozen Bolzano EURAC, Ctr Biomed, Bolzano, Italy.
   Med Univ Lubeck, Lubeck, Germany.
   Zanigni, Stefano; Pramstaller, Peter P., Gen Cent Hosp, Dept Neurol, Bolzano, Italy.
   Cortelli, Pietro, Alma Mater Studiorum Univ Bologna, IRCCS Inst Neurol Sci Bologna, Bologna, Italy.
   Cortelli, Pietro, Alma Mater Studiorum Univ Bologna, Dept Biomed \& NeuroMotor Sci, Bologna, Italy.
   Pramstaller, Peter P., Med Univ Lubeck, Dept Neurol, Lubeck, Germany.}},
DOI = {{10.1212/WNL.0000000000001258}},
ISSN = {{0028-3878}},
EISSN = {{1526-632X}},
Keywords-Plus = {{REAL-TIME PCR; PARKINSONS-DISEASE; CANDIDATE GENES; TARGETS; EXPRESSION;
   PATHOGENESIS; PREDICTION; MODEL}},
Research-Areas = {{Neurosciences \& Neurology}},
Web-of-Science-Categories  = {{Clinical Neurology}},
Author-Email = {{christine.schwienbacher@eurac.edu}},
ORCID-Numbers = {{ZANIGNI, STEFANO/0000-0003-4071-0886
   Cortelli, Pietro/0000-0002-3633-8818}},
Funding-Acknowledgement = {{Department for Promotion of Educational Policies, Universities and
   Research of the Autonomous Province of Bolzano, South Tyrol; South
   Tyrolean Sparkasse Foundation}},
Funding-Text = {{This work was supported by the Department for Promotion of Educational
   Policies, Universities and Research of the Autonomous Province of
   Bolzano, South Tyrol, and the South Tyrolean Sparkasse Foundation.}},
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Number-of-Cited-References = {{41}},
Times-Cited = {{8}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{Neurology}},
Doc-Delivery-Number = {{CB7XV}},
Unique-ID = {{ISI:000349843000008}},
}

@article{ ISI:000353974600006,
Author = {Wang, Wenhui and Zhou, Xianghong Jasmine and Liu, Zhenqiu and Sun,
   Fengzhu},
Title = {{Network tuned multiple rank aggregation and applications to gene ranking}},
Journal = {{BMC BIOINFORMATICS}},
Year = {{2015}},
Volume = {{16}},
Number = {{1}},
Month = {{JAN 21}},
Abstract = {{With the development of various high throughput technologies and
   analysis methods, researchers can study different aspects of a
   biological phenomenon simultaneously or one aspect repeatedly with
   different experimental techniques and analysis methods. The output from
   each study is a rank list of components of interest. Aggregation of the
   rank lists of components, such as proteins, genes and single nucleotide
   variants (SNV), produced by these experiments has been proven to be
   helpful in both filtering the noise and bringing forth a more complete
   understanding of the biological problems. Current available rank
   aggregation methods do not consider the network information that has
   been observed to provide vital contributions in many data integration
   studies. We developed network tuned rank aggregation methods
   incorporating network information and demonstrated its superior
   performance over aggregation methods without network information.
   The methods are tested on predicting the Gene Ontology function of yeast
   proteins. We validate the methods using combinations of three gene
   expression data sets and three protein interaction networks as well as
   an integrated network by combining the three networks. Results show that
   the aggregated rank lists are more meaningful if protein interaction
   network is incorporated. Among the methods compared, CGI\_RRA and
   CGI\_Endeavour, which integrate rank lists with networks using CGI {[}1]
   followed by rank aggregation using either robust rank aggregation (RRA)
   {[}2] or Endeavour {[}3] perform the best. Finally, we use the methods
   to locate target genes of transcription factors.}},
Publisher = {{BIOMED CENTRAL LTD}},
Address = {{236 GRAYS INN RD, FLOOR 6, LONDON WC1X 8HL, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Sun, FZ (Reprint Author), Univ So Calif, Mol \& Computat Biol Program, 1050 Childs Way, Los Angeles, CA 90089 USA.
   Wang, Wenhui; Zhou, Xianghong Jasmine; Sun, Fengzhu, Univ So Calif, Mol \& Computat Biol Program, Los Angeles, CA 90089 USA.
   Liu, Zhenqiu, Cedars Sinai Med Ctr, Samuel Oschin Comprehens Canc Inst, Los Angeles, CA 90048 USA.
   Sun, Fengzhu, Fudan Univ, Sch Math Sci, Ctr Computat Syst Biol, Shanghai 200433, Peoples R China.}},
DOI = {{10.1186/1471-2105-16-S1-S6}},
Article-Number = {{S6}},
ISSN = {{1471-2105}},
Keywords-Plus = {{SACCHAROMYCES-CEREVISIAE; DATA INTEGRATION; CELL-CYCLE; EXPRESSION;
   PRIORITIZATION; DISCOVERY}},
Research-Areas = {{Biochemistry \& Molecular Biology; Biotechnology \& Applied
   Microbiology; Mathematical \& Computational Biology}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Biotechnology \& Applied Microbiology;
   Mathematical \& Computational Biology}},
Author-Email = {{fsun@usc.edu}},
ResearcherID-Numbers = {{Sun, Fengzhu /G-4373-2010}},
Funding-Acknowledgement = {{US National Institutes of Health Center for Excellence in Genomic
   Sciences {[}P50HG002790]; MAPGen Consortium from the National Heart,
   Lung, and Blood Institute {[}U01HL108630]}},
Funding-Text = {{This work was partially supported by the US National Institutes of
   Health Center for Excellence in Genomic Sciences {[}P50HG002790] and the
   MAPGen Consortium {[}U01HL108630] from the National Heart, Lung, and
   Blood Institute. The authors thank the reviewers for their constructive
   comments.}},
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Number-of-Cited-References = {{37}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{BMC Bioinformatics}},
Doc-Delivery-Number = {{CH4BA}},
Unique-ID = {{ISI:000353974600006}},
}

@article{ ISI:000347832300009,
Author = {Badgeley, Marcus A. and Sealfon, Stuart C. and Chikina, Maria D.},
Title = {{Hybrid Bayesian-rank integration approach improves the predictive power
   of genomic dataset aggregation}},
Journal = {{BIOINFORMATICS}},
Year = {{2015}},
Volume = {{31}},
Number = {{2}},
Pages = {{209-215}},
Month = {{JAN 15}},
Abstract = {{Motivation: Modern molecular technologies allow the collection of large
   amounts of high-throughput data on the functional attributes of genes.
   Often multiple technologies and study designs are used to address the
   same biological question such as which genes are over-expressed in a
   specific disease state. Consequently, there is considerable interest in
   methods that can integrate across datasets to present a unified set of
   predictions.
   Results: An important aspect of data integration is being able to
   account for the fact that datasets may differ in how accurately they
   capture the biological signal of interest. While many methods to address
   this problem exist, they always rely either on dataset internal
   statistics, which reflect data structure and not necessarily biological
   relevance, or external gold standards, which may not always be
   available. We present a new rank aggregation method for data integration
   that requires neither external standards nor internal statistics but
   relies on Bayesian reasoning to assess dataset relevance. We demonstrate
   that our method outperforms established techniques and significantly
   improves the predictive power of rank-based aggregations. We show that
   our method, which does not require an external gold standard, provides
   reliable estimates of dataset relevance and allows the same set of data
   to be integrated differently depending on the specific signal of
   interest.}},
Publisher = {{OXFORD UNIV PRESS}},
Address = {{GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Chikina, MD (Reprint Author), Univ Pittsburgh, Dept Computat \& Syst Biol, Pittsburgh, PA 15260 USA.
   Badgeley, Marcus A.; Sealfon, Stuart C., Mt Sinai Hosp, Dept Neurol, New York, NY 10029 USA.
   Chikina, Maria D., Univ Pittsburgh, Dept Computat \& Syst Biol, Pittsburgh, PA 15260 USA.}},
DOI = {{10.1093/bioinformatics/btu518}},
ISSN = {{1367-4803}},
EISSN = {{1460-2059}},
Keywords-Plus = {{EMBRYONIC STEM-CELLS; GENE-EXPRESSION; NETWORK; METAANALYSIS}},
Research-Areas = {{Biochemistry \& Molecular Biology; Biotechnology \& Applied
   Microbiology; Computer Science; Mathematical \& Computational Biology;
   Mathematics}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Biotechnology \& Applied Microbiology;
   Computer Science, Interdisciplinary Applications; Mathematical \&
   Computational Biology; Statistics \& Probability}},
Author-Email = {{mchikina@pitt.edu}},
Funding-Acknowledgement = {{NIH {[}HHSN272201000054C]; Michael J Fox Foundation}},
Funding-Text = {{Funded by NIH Contract HHSN272201000054C and a grant from the Michael J
   Fox Foundation.}},
Cited-References = {{Akey JM, 2007, NAT GENET, V39, P807, DOI 10.1038/ng0707-807.
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   Zheng B, 2010, SCI TRANSL MED, V2, DOI 10.1126/scitranslmed.3001059.}},
Number-of-Cited-References = {{15}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{Bioinformatics}},
Doc-Delivery-Number = {{AY8WU}},
Unique-ID = {{ISI:000347832300009}},
}

@article{ ISI:000366867300001,
Author = {Singh, Jagendra and Sharan, Aditi},
Title = {{Relevance Feedback Based Query Expansion Model Using Borda Count and
   Semantic Similarity Approach}},
Journal = {{COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE}},
Year = {{2015}},
Abstract = {{Pseudo-Relevance Feedback (PRF) is a well-known method of query
   expansion for improving the performance of information retrieval
   systems. All the terms of PRF documents are not important for expanding
   the user query. Therefore selection of proper expansion term is very
   important for improving system performance. Individual query expansion
   terms selection methods have been widely investigated for improving its
   performance. Every individual expansion term selection method has its
   own weaknesses and strengths. To overcome the weaknesses and to utilize
   the strengths of the individual method, we used multiple terms selection
   methods together. In this paper, first the possibility of improving the
   overall performance using individual query expansion terms selection
   methods has been explored. Second, Borda count rank aggregation approach
   is used for combining multiple query expansion terms selection methods.
   Third, the semantic similarity approach is used to select semantically
   similar terms with the query after applying Borda count ranks combining
   approach. Our experimental results demonstrated that our proposed
   approaches achieved a significant improvement over individual terms
   selection method and related state-of-the-art methods.}},
Publisher = {{HINDAWI PUBLISHING CORP}},
Address = {{410 PARK AVENUE, 15TH FLOOR, \#287 PMB, NEW YORK, NY 10022 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Singh, J (Reprint Author), Jawaharlal Nehru Univ, Sch Comp \& Syst Sci, New Delhi 110067, India.
   Singh, Jagendra; Sharan, Aditi, Jawaharlal Nehru Univ, Sch Comp \& Syst Sci, New Delhi 110067, India.}},
DOI = {{10.1155/2015/568197}},
Article-Number = {{568197}},
ISSN = {{1687-5265}},
EISSN = {{1687-5273}},
Keywords-Plus = {{INFORMATION-RETRIEVAL; SELECTION; SYSTEMS}},
Research-Areas = {{Mathematical \& Computational Biology; Neurosciences \& Neurology}},
Web-of-Science-Categories  = {{Mathematical \& Computational Biology; Neurosciences}},
Author-Email = {{jagendrasngh@gmail.com}},
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Number-of-Cited-References = {{26}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{0}},
Journal-ISO = {{Comput. Intell. Neurosci.}},
Doc-Delivery-Number = {{CZ1LM}},
Unique-ID = {{ISI:000366867300001}},
}

@article{ ISI:000359544100001,
Author = {Cui, Zhijie and Kang, Hong and Tang, Kailin and Liu, Qi and Cao, Zhiwei
   and Zhu, Ruixin},
Title = {{Screening Ingredients from Herbs against Pregnane X Receptor in the
   Study of Inductive Herb-Drug Interactions: Combining Pharmacophore and
   Docking-Based Rank Aggregation}},
Journal = {{BIOMED RESEARCH INTERNATIONAL}},
Year = {{2015}},
Abstract = {{The issue of herb-drug interactions has been widely reported. Herbal
   ingredients can activate nuclear receptors and further induce the gene
   expression alteration of drug-metabolizing enzyme and/or transporter.
   Therefore, the herb-drug interaction will happen when the herbs and
   drugs are coadministered. This kind of interaction is called inductive
   herb-drug interactions. Pregnane X Receptor (PXR) and drug-metabolizing
   target genes are involved in most of inductive herb-drug interactions.
   To predict this kind of herb-drug interaction, the protocol could be
   simplified to only screen agonists of PXR from herbs because the
   relations of drugs with their metabolizing enzymes are well studied.
   Here, a combinational in silico strategy of pharmacophore modelling and
   docking-based rank aggregation (DRA) was employed to identify PXR's
   agonists. Firstly, 305 ingredients were screened out from 820
   ingredients as candidate agonists of PXR with our pharmacophore model.
   Secondly, DRA was used to rerank the result of pharmacophore filtering.
   To validate our prediction, a curated herb-drug interaction database was
   built, which recorded 380 herb-drug interactions. Finally, among the top
   10 herb ingredients from the ranking list, 6 ingredients were reported
   to involve in herb-drug interactions. The accuracy of our method is
   higher than other traditional methods. The strategy could be extended to
   studies on other inductive herb-drug interactions.}},
Publisher = {{HINDAWI PUBLISHING CORPORATION}},
Address = {{410 PARK AVENUE, 15TH FLOOR, \#287 PMB, NEW YORK, NY 10022 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Cao, ZW (Reprint Author), Tongji Univ, Dept Bioinformat, Shanghai 200092, Peoples R China.
   Cui, Zhijie; Kang, Hong; Tang, Kailin; Liu, Qi; Cao, Zhiwei; Zhu, Ruixin, Tongji Univ, Dept Bioinformat, Shanghai 200092, Peoples R China.
   Cao, Zhiwei, Shanghai Ctr Bioinformat Technol, Shanghai, Peoples R China.
   Zhu, Ruixin, Liaoning Univ Tradit Chinese Med, Sch Pharm, Dalian, Liaoning, Peoples R China.}},
DOI = {{10.1155/2015/657159}},
Article-Number = {{657159}},
ISSN = {{2314-6133}},
EISSN = {{2314-6141}},
Keywords-Plus = {{CONSTITUTIVE ANDROSTANE RECEPTOR; IN-SILICO; NUCLEAR RECEPTORS;
   NATURAL-PRODUCTS; LIGAND; PXR; THEOPHYLLINE; METABOLISM; PROTEIN; RATS}},
Research-Areas = {{Biotechnology \& Applied Microbiology; Research \& Experimental Medicine}},
Web-of-Science-Categories  = {{Biotechnology \& Applied Microbiology; Medicine, Research \&
   Experimental}},
Author-Email = {{zwcao@tongji.edu.cn
   rxzhu@tongji.edu.cn}},
Funding-Acknowledgement = {{National Natural Science Foundation of China {[}30976611, 31171272];
   Fundamental Research Funds for the Central Universities {[}2000219083]}},
Funding-Text = {{This work was supported by National Natural Science Foundation of China
   30976611 (to RZ) and 31171272 (to WZ) and the Fundamental Research Funds
   for the Central Universities 2000219083 (to RZ). The funders had no role
   in study design, data collection and analysis, decision to publish, or
   preparation of the paper.}},
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Number-of-Cited-References = {{49}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{8}},
Usage-Count-Since-2013 = {{8}},
Journal-ISO = {{Biomed Res. Int.}},
Doc-Delivery-Number = {{CP0CT}},
Unique-ID = {{ISI:000359544100001}},
}

@article{ ISI:000351002900006,
Author = {Mersmann, O. and Preuss, M. and Trautmann, H. and Bischl, B. and Weihs,
   C.},
Title = {{Analyzing the BBOB Results by Means of Benchmarking Concepts}},
Journal = {{EVOLUTIONARY COMPUTATION}},
Year = {{2015}},
Volume = {{23}},
Number = {{1}},
Pages = {{161-185}},
Abstract = {{We present methods to answer two basic questions that arise when
   benchmarking optimization algorithms. The first one is: which algorithm
   is the ``best{''} one? and the second one is: which algorithm should I
   use for my real-world problem? Both are connected and neither is easy to
   answer. We present a theoretical framework for designing and analyzing
   the raw data of such benchmark experiments. This represents a first step
   in answering the aforementioned questions. The 2009 and 2010 BBOB
   benchmark results are analyzed by means of this framework and we derive
   insight regarding the answers to the two questions. Furthermore, we
   discuss how to properly aggregate rankings from algorithm evaluations on
   individual problems into a consensus, its theoretical background and
   which common pitfalls should be avoided. Finally, we address the
   grouping of test problems into sets with similar optimizer rankings and
   investigate whether these are reflected by already proposed test problem
   characteristics, finding that this is not always the case.}},
Publisher = {{MIT PRESS}},
Address = {{ONE ROGERS ST, CAMBRIDGE, MA 02142-1209 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Mersmann, O (Reprint Author), TU Dortmund Univ, Chair Computat Stat, Dortmund, Germany.
   Mersmann, O.; Bischl, B.; Weihs, C., TU Dortmund Univ, Chair Computat Stat, Dortmund, Germany.
   Preuss, M.; Trautmann, H., Univ Munster, Chair Informat Syst \& Stat, Munster, Germany.}},
DOI = {{10.1162/EVCO\_a\_00134}},
ISSN = {{1063-6560}},
EISSN = {{1530-9304}},
Keywords = {{Evolutionary optimization; benchmarking; exploratory landscape analysis;
   BBOB test set; multidimensional scaling; consensus ranking}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Computer Science, Theory \&
   Methods}},
Author-Email = {{olafm@statistik.tu-dortmund.de
   mike.preuss@uni-muenster.de
   trautmann@wi.uni-muenster.de
   bischl@statistik.tu-dortmund.de
   weihs@statistik.tu-dortmund.de}},
Funding-Acknowledgement = {{Collaborative Research Center {[}SFB 823]; Graduate School of Energy
   Efficient Production and Logistics; Research Training Group
   ``Statistical Modelling{''} of the German Research Foundation}},
Funding-Text = {{This work was partly supported by the Collaborative Research Center SFB
   823, the Graduate School of Energy Efficient Production and Logistics
   and the Research Training Group ``Statistical Modelling{''} of the
   German Research Foundation.}},
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   Mood A. M., 1974, INTRO THEORY STAT.}},
Number-of-Cited-References = {{24}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Evol. Comput.}},
Doc-Delivery-Number = {{CD3TA}},
Unique-ID = {{ISI:000351002900006}},
}

@article{ ISI:000347297500016,
Author = {Evison, David C. and Apiolaza, Luis A.},
Title = {{Incorporating economic weights into radiata pine breeding selection
   decisions}},
Journal = {{CANADIAN JOURNAL OF FOREST RESEARCH}},
Year = {{2015}},
Volume = {{45}},
Number = {{1}},
Pages = {{135-140}},
Month = {{JAN}},
Abstract = {{This article introduces the concept of ``robust selection{''}, which
   proposes tree selection based on the stochastic simulation of economic
   values to account for the inherent uncertainty of economic weights used
   in tree selection for breeding programs. The proposed method uses both
   median ranking and ranking variability as criteria for breeding
   selection. Using consensus genetic and economic parameters from the New
   Zealand Radiata Pine Breeding Company program, we compare three
   selection strategies: deterministic application of economic weights from
   a vertically integrated bioeconomic model, an equal-weight index often
   used in operations, and robust selection. All strategies aim to increase
   value for a breeding objective that includes four traits, i.e., volume,
   stem sweep, branch size, and wood stiffness (measured as modulus of
   elasticity), based on a selection index that considers five criteria,
   i.e., stem diameter at breast height (1.3 m), straightness, branching
   score, wood density, and modulus of elasticity. Two-thirds of the
   selected trees were unique for each of the selection strategies. Robust
   selection achieved the best realised gain for three of the four
   selection criteria and was the middle performer in the last selection
   criteria. Considering the high intrinsic uncertainty of economic
   weights, we suggest that the relevant criterion for the selection of
   individuals is the maximum median ranking, subject to an acceptable
   level of variation in that ranking, rather than their narrow performance
   under a single economic scenario. This will lead to tree selections that
   perform well under a wide range of economic circumstances.}},
Publisher = {{CANADIAN SCIENCE PUBLISHING, NRC RESEARCH PRESS}},
Address = {{65 AURIGA DR, SUITE 203, OTTAWA, ON K2E 7W6, CANADA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Evison, DC (Reprint Author), Univ Canterbury, Sch Forestry, Private Bag 4800, Christchurch 1, New Zealand.
   Evison, David C.; Apiolaza, Luis A., Univ Canterbury, Sch Forestry, Christchurch 1, New Zealand.}},
DOI = {{10.1139/cjfr-2014-0363}},
ISSN = {{0045-5067}},
EISSN = {{1208-6037}},
Keywords = {{breeding objectives; economic weights; simulation; economic evaluation;
   risk analysis}},
Keywords-Plus = {{OBJECTIVES; INDEXES; MODEL}},
Research-Areas = {{Forestry}},
Web-of-Science-Categories  = {{Forestry}},
Author-Email = {{David.Evison@canterbury.ac.nz}},
ORCID-Numbers = {{Apiolaza, Luis/0000-0003-0958-3540}},
Funding-Acknowledgement = {{Radiata Pine Breeding Company Ltd.; Technical Committee of the Radiata
   Pine Breeding Company}},
Funding-Text = {{This research was funded by the Radiata Pine Breeding Company Ltd. The
   support of John Butcher, Paul Jefferson, and the Technical Committee of
   the Radiata Pine Breeding Company is gratefully acknowledged.}},
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Number-of-Cited-References = {{16}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{9}},
Journal-ISO = {{Can. J. For. Res.}},
Doc-Delivery-Number = {{AY0PA}},
Unique-ID = {{ISI:000347297500016}},
}

@article{ ISI:000347515300049,
Author = {Yang, Jingcheng and Han, Shuai and Huang, Wenwen and Chen, Ting and Liu,
   Yang and Pan, Shangling and Li, Shikang},
Title = {{A Meta-Analysis of MicroRNA Expression in Liver Cancer}},
Journal = {{PLOS ONE}},
Year = {{2014}},
Volume = {{9}},
Number = {{12}},
Month = {{DEC 9}},
Abstract = {{MicroRNA (miRNA) played an important role in the progression of liver
   cancer and its diagnostic and prognostic values have been frequently
   studied. However, different microarray techniques and small sample size
   led to inconsistent findings in previous studies. We performed a
   comprehensive meta-analysis of a total of 357 tumor and 283 noncancerous
   samples from 12 published miRNA expression studies using robust rank
   aggregation method. As a result, we identified a statistically
   significant meta-signature of five upregulated (miR-221, miR-222,
   miR-93, miR-21 and miR-224) and four downregulated (miR-130a, miR-195,
   miR-199a and miR-375) miRNAs. We then conducted miRNA target prediction
   and pathway enrichment analysis to find what biological process these
   miRNAs might affect. We found that most of the pathways were frequently
   associated with cell signaling and cancer pathogenesis. Thus these
   miRNAs may involve in the onset and progression of liver cancer and
   serve as potential diagnostic and therapeutic targets of this
   malignancy.}},
Publisher = {{PUBLIC LIBRARY SCIENCE}},
Address = {{1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Li, SK (Reprint Author), Guangxi Med Univ, Affiliated Hosp 1, Nanning, Guangxi Zhuang, Peoples R China.
   Yang, Jingcheng; Han, Shuai; Huang, Wenwen; Liu, Yang; Li, Shikang, Guangxi Med Univ, Affiliated Hosp 1, Nanning, Guangxi Zhuang, Peoples R China.
   Chen, Ting, Guangxi Teachers Educ Univ, Coll Comp \& Informat Engn, Dept Management Informat Syst, Nanning, Guangxi Zhuang, Peoples R China.
   Pan, Shangling, Guangxi Med Univ, Dept Pathophysiol, Nanning, Guangxi Zhuang, Peoples R China.}},
DOI = {{10.1371/journal.pone.0114533}},
Article-Number = {{e114533}},
ISSN = {{1932-6203}},
Keywords-Plus = {{HUMAN HEPATOCELLULAR-CARCINOMA; TUMOR-SUPPRESSOR; GENE; CELLS; MIR-221;
   TUMORIGENICITY; APOPTOSIS; TARGETS; PROTEIN; MIRNA}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{shikangli@hotmail.com}},
Funding-Acknowledgement = {{Research Project of Guangxi Colleges and Universities {[}201203YB035];
   Guangxi Key Project of Science and Technology {[}1355005-4-8]}},
Funding-Text = {{This study was funded by Research Project of Guangxi Colleges and
   Universities (201203YB035) and Guangxi Key Project of Science and
   Technology (1355005-4-8). The funders had no role in study design, data
   collection and analysis, decision to publish, or preparation of the
   manuscript.}},
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Number-of-Cited-References = {{51}},
Times-Cited = {{3}},
Usage-Count-(Last-180-days) = {{5}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{PLoS One}},
Doc-Delivery-Number = {{AY3YM}},
Unique-ID = {{ISI:000347515300049}},
}

@article{ ISI:000348646000012,
Author = {Vermeirssen, Vanessa and De Clercq, Inge and Van Parys, Thomas and Van
   Breusegem, Frank and Van de Peer, Yves},
Title = {{Arabidopsis Ensemble Reverse-Engineered Gene Regulatory Network
   Discloses Interconnected Transcription Factors in Oxidative Stress}},
Journal = {{PLANT CELL}},
Year = {{2014}},
Volume = {{26}},
Number = {{12}},
Pages = {{4656-4679}},
Month = {{DEC}},
Abstract = {{The abiotic stress response in plants is complex and tightly controlled
   by gene regulation. We present an abiotic stress gene regulatory network
   of 200,014 interactions for 11,938 target genes by integrating four
   complementary reverse-engineering solutions through average rank
   aggregation on an Arabidopsis thaliana microarray expression compendium.
   This ensemble performed the most robustly in benchmarking and greatly
   expands upon the availability of interactions currently reported.
   Besides recovering 1182 known regulatory interactions, cis-regulatory
   motifs and coherent functionalities of target genes corresponded with
   the predicted transcription factors. We provide a valuable resource of
   572 abiotic stress modules of coregulated genes with functional and
   regulatory information, from which we deduced functional relationships
   for 1966 uncharacterized genes and many regulators. Using gain-and
   loss-of-function mutants of seven transcription factors grown under
   control and salt stress conditions, we experimentally validated 141 out
   of 271 predictions (52\% precision) for 102 selected genes and mapped
   148 additional transcription factor-gene regulatory interactions (49\%
   recall). We identified an intricate core oxidative stress regulatory
   network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription
   factors interconnect and function in detoxification. Our work shows that
   ensemble reverse-engineering can generate robust biological hypotheses
   of gene regulation in a multicellular eukaryote that can be tested by
   medium-throughput experimental validation.}},
Publisher = {{AMER SOC PLANT BIOLOGISTS}},
Address = {{15501 MONONA DRIVE, ROCKVILLE, MD 20855 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Vermeirssen, V (Reprint Author), VIB, Dept Plant Syst Biol, B-9052 Ghent, Belgium.
   Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves, VIB, Dept Plant Syst Biol, B-9052 Ghent, Belgium.
   Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves, Univ Ghent, Dept Plant Biotechnol \& Bioinformat, B-9052 Ghent, Belgium.
   Van de Peer, Yves, Univ Pretoria, Genom Res Inst, ZA-0028 Pretoria, South Africa.}},
DOI = {{10.1105/tpc.114.131417}},
ISSN = {{1040-4651}},
EISSN = {{1532-298X}},
Keywords-Plus = {{DIFFERENTIAL EXPRESSION ANALYSIS; AMINO-ACID-METABOLISM; ABIOTIC STRESS;
   SALICYLIC-ACID; SYSTEMS BIOLOGY; RESPONSIVE TRANSCRIPTION; ENCODING
   MITOCHONDRIAL; COEXPRESSION ANALYSIS; RETROGRADE REGULATION; PROTEIN
   RESPONSE}},
Research-Areas = {{Biochemistry \& Molecular Biology; Plant Sciences; Cell Biology}},
Web-of-Science-Categories  = {{Biochemistry \& Molecular Biology; Plant Sciences; Cell Biology}},
Author-Email = {{vanessa.vermeirssen@psb.vib-ugent.be}},
ResearcherID-Numbers = {{Van de Peer, Yves/D-4388-2009
   }},
ORCID-Numbers = {{Van de Peer, Yves/0000-0003-4327-3730
   Van Breusegem, Frank/0000-0002-3147-0860}},
Funding-Acknowledgement = {{Ghent University Multidisciplinary Research Partnership {[}01MR0310W]}},
Funding-Text = {{We thank the following people for fruitful discussions: Jens Hollunder
   on integration of reverse-engineering solutions, Bram Slabbinck on
   performance assessment of network inference and ModuleViewer, Frederik
   Coppens on the NanoString nCounter experimental setup, and Eric Bonnet
   on the combination of network inference with experimental validation by
   nCounter. WRKY6\_OE lines were kindly provided by Wei-Hua Wu;
   NAC13\_ami, NAC32\_KO, NAC53\_KO, and NAC overexpression lines by Frank
   Hoeberichts and Sandy Vanderauwera; and the ERF6\_OE line by Marieke
   Dubois. Cezary Waszczak helped sort out transgenic lines. Debbie Rombout
   and Brigitte Van De Cotte delivered excellent technical assistance. This
   work was supported by grants from Ghent University Multidisciplinary
   Research Partnership ({''} Bioinformatics: from nucleotides to
   networks{''} {[}Project 01MR0310W] and `` Ghent BioEconomy{''}
   {[}Project 01MRB510W]) and VIB ( Technology Watch Fund for nCounter). I.
   D. C. is indebted to the Research Foundation-Flanders for a postdoctoral
   fellowship.}},
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Number-of-Cited-References = {{167}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{15}},
Usage-Count-Since-2013 = {{32}},
Journal-ISO = {{Plant Cell}},
Doc-Delivery-Number = {{CA1AW}},
Unique-ID = {{ISI:000348646000012}},
}

@article{ ISI:000347277000015,
Author = {Bian, Jiang and Xie, Mengjun and Topaloglu, Umit and Hudson, Teresa and
   Eswaran, Hari and Hogan, William},
Title = {{Social network analysis of biomedical research collaboration networks in
   a CTSA institution}},
Journal = {{JOURNAL OF BIOMEDICAL INFORMATICS}},
Year = {{2014}},
Volume = {{52}},
Pages = {{130-140}},
Month = {{DEC}},
Abstract = {{Background: The popularity of social networks has triggered a number of
   research efforts on network analyses of research collaborations in the
   Clinical and Translational Science Award (CTSA) community. Those studies
   mainly focus on the general understanding of collaboration networks by
   measuring common network metrics. More fundamental questions about
   collaborations still remain unanswered such as recognizing
   ``influential{''} nodes and identifying potential new collaborations
   that are most rewarding.
   Methods: We analyzed biomedical research collaboration networks (RCNs)
   constructed from a dataset of research grants collected at a CTSA
   institution (i.e., University of Arkansas for Medical Sciences (UAMS))
   in a comprehensive and systematic manner. First, our analysis covers the
   full spectrum of a RCN study: from network modeling to network
   characteristics measurement, from key nodes recognition to potential
   links (collaborations) suggestion. Second, our analysis employs
   non-conventional model and techniques including a weighted network model
   for representing collaboration strength, rank aggregation for detecting
   important nodes, and Random Walk with Restart (RWR) for suggesting new
   research collaborations.
   Results: By applying our models and techniques to RCNs at UAMS prior to
   and after the CTSA, we have gained valuable insights that not only
   reveal the temporal evolution of the network dynamics but also assess
   the effectiveness of the CTSA and its impact on a research institution.
   We find that collaboration networks at UAMS are not scale-free but
   small-world. Quantitative measures have been obtained to evident that
   the RCNs at UAMS are moving towards favoring multidisciplinary research.
   Moreover, our link prediction model creates the basis of collaboration
   recommendations with an impressive accuracy (AUC: 0.990, MAP@3: 1.48 and
   MAP@5: 1.522). Last but not least, an open-source visual analytical tool
   for RCNs is being developed and released through Gi thub.
   Conclusions: Through this study, we have developed a set of techniques
   and tools for analyzing research collaboration networks and conducted a
   comprehensive case study focusing on a CTSA institution. Our findings
   demonstrate the promising future of these techniques and tools in
   understanding the generative mechanisms of research collaborations and
   helping identify beneficial collaborations to members in the research
   community. Published by Elsevier Inc.}},
Publisher = {{ACADEMIC PRESS INC ELSEVIER SCIENCE}},
Address = {{525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Bian, J (Reprint Author), Univ Arkansas Med Sci, Div Biomed Informat, Little Rock, AR 72205 USA.
   Bian, Jiang; Topaloglu, Umit; Eswaran, Hari; Hogan, William, Univ Arkansas Med Sci, Div Biomed Informat, Little Rock, AR 72205 USA.
   Xie, Mengjun, Univ Arkansas, Little Rock, AR 72204 USA.
   Eswaran, Hari, Univ Arkansas Med Sci, Little Rock, AR 72205 USA.
   Hudson, Teresa, Univ Arkansas Med Sci, Dept Psychiat, Little Rock, AR 72205 USA.
   Hudson, Teresa, Cent Arkansas Vet Healthcare Syst, Little Rock, AR 72205 USA.}},
DOI = {{10.1016/j.jbi.2014.01.015}},
ISSN = {{1532-0464}},
EISSN = {{1532-0480}},
Keywords = {{Research collaboration network; Network analysis; Clinical and
   Translational Science Award (CTSA); Link prediction; Influential node;
   Small-world}},
Keywords-Plus = {{SMALL-WORLD; SCIENTIFIC COLLABORATION; CENTRALITY; POWER}},
Research-Areas = {{Computer Science; Medical Informatics}},
Web-of-Science-Categories  = {{Computer Science, Interdisciplinary Applications; Medical Informatics}},
Author-Email = {{jbian@uams.edu
   mxxie@ualr.edu
   utopaloglu@uams.edu
   HudsonTeresaJ@uams.edu
   EswaranHari@uams.edu
   wrhogan@uams.edu}},
ORCID-Numbers = {{Hogan, William/0000-0002-9881-1017}},
Funding-Acknowledgement = {{National Center for Advancing Translational Sciences {[}UL1TR000039]}},
Funding-Text = {{The work described in this manuscript is supported by award UL1TR000039
   through National Center for Advancing Translational Sciences (formerly
   UL1RR029884 through the NIH National Center for Research Resources). The
   content is solely the responsibility of the authors and does not
   necessarily represent the official views of the NIH.}},
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Number-of-Cited-References = {{33}},
Times-Cited = {{5}},
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Journal-ISO = {{J. Biomed. Inform.}},
Doc-Delivery-Number = {{AY0HC}},
Unique-ID = {{ISI:000347277000015}},
}

@article{ ISI:000345099200018,
Author = {Shah, Jasmit and Datta, Somnath and Datta, Susmita},
Title = {{A multi-loss super regression learner (MSRL) with application to
   survival prediction using proteomics}},
Journal = {{COMPUTATIONAL STATISTICS}},
Year = {{2014}},
Volume = {{29}},
Number = {{6}},
Pages = {{1749-1767}},
Month = {{DEC}},
Abstract = {{Even though a number of regression techniques have been proposed over
   the years to handle a large number of regressors, due to the complex
   nature of data emerging from recent high-throughput experiments, it is
   unlikely that any single technique will be successful in modeling all
   data types. Thus, multiple regression algorithms from the collection of
   modern regression techniques that are capable of handling high
   dimensional regressors should be entertained for analyzing such data. A
   novel approach of building a super regression learner is proposed which
   can be fit with a training data set in order to make future predictions
   of a continuous outcome. The resulting super regression model is
   multi-objective in nature and mimics the performances of the best
   component regression models irrespective of the data type. This is
   accomplished by combining elements of bootstrap based risk calculation,
   rank aggregation, and stacking. The utility of this approach is
   demonstrated through its use on mass spectrometry data.}},
Publisher = {{SPRINGER HEIDELBERG}},
Address = {{TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Datta, S (Reprint Author), Univ Louisville, Dept Bioinformat \& Biostat, Louisville, KY 40292 USA.
   Shah, Jasmit; Datta, Somnath; Datta, Susmita, Univ Louisville, Dept Bioinformat \& Biostat, Louisville, KY 40292 USA.}},
DOI = {{10.1007/s00180-014-0516-z}},
ISSN = {{0943-4062}},
EISSN = {{1613-9658}},
Keywords = {{Bagging; Rank aggregation; Regression}},
Keywords-Plus = {{CELL LUNG-CANCER; PARTIAL LEAST-SQUARES; MASS-SPECTROMETRY; SELECTION;
   CHEMOTHERAPY; ENSEMBLES; REGIMENS; MODELS}},
Research-Areas = {{Mathematics}},
Web-of-Science-Categories  = {{Statistics \& Probability}},
Author-Email = {{jasmit.shah@louisville.edu
   somnath.datta@louisville.edu
   susmita.datta@louisville.edu}},
Funding-Acknowledgement = {{National Science Foundation {[}NSF-DMS-0805559, NSF-DMS-1125909];
   National Institutes of Health {[}NIH-CA133844]}},
Funding-Text = {{This research was supported in part by grants from National Science
   Foundation (NSF-DMS-0805559, NSF-DMS-1125909) and the National
   Institutes of Health (NIH-CA133844). We thankfully acknowledge Johannes
   Voortman and Thang V. Pham for graciously sharing the Netherlands NSCLC
   data with us. We thank two anonymous reviewers for numerous constructive
   suggestions leading to a much better paper.}},
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Number-of-Cited-References = {{41}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{Comput. Stat.}},
Doc-Delivery-Number = {{AT7EH}},
Unique-ID = {{ISI:000345099200018}},
}

@article{ ISI:000344754500004,
Author = {Dekel (Basha), Tali and Moses, Yael and Avidan, Shai},
Title = {{Photo Sequencing}},
Journal = {{INTERNATIONAL JOURNAL OF COMPUTER VISION}},
Year = {{2014}},
Volume = {{110}},
Number = {{3, SI}},
Pages = {{275-289}},
Month = {{DEC}},
Abstract = {{A group of people taking pictures of a dynamic event with their mobile
   phones is a popular sight. The set of still images obtained this way is
   rich in dynamic content but lacks accurate temporal information. We
   propose a method for photo-sequencing-temporally ordering a set of still
   images taken asynchronously by a set of uncalibrated cameras.
   Photo-sequencing is an essential tool in analyzing (or visualizing) a
   dynamic scene captured by still images. The first step of the method
   detects sets of corresponding static and dynamic feature points across
   images. The static features are used to determine the epipolar geometry
   between pairs of images, and each dynamic feature votes for the temporal
   order of the images in which it appears. The partial orders provided by
   the dynamic features are not necessarily consistent, and we use rank
   aggregation to combine them into a globally consistent temporal order of
   images. We demonstrate successful photo-sequencing on several
   challenging collections of images taken using a number of mobile phones.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Dekel, T (Reprint Author), Tel Aviv Univ, Sch Elect Engn, IL-69978 Tel Aviv, Israel.
   Dekel (Basha), Tali; Avidan, Shai, Tel Aviv Univ, Sch Elect Engn, IL-69978 Tel Aviv, Israel.
   Moses, Yael, Interdisciplinary Ctr, Efi Arazi Sch Comp Sci, IL-46150 Herzliyya, Israel.}},
DOI = {{10.1007/s11263-014-0712-x}},
ISSN = {{0920-5691}},
EISSN = {{1573-1405}},
Keywords-Plus = {{TRAJECTORY TRIANGULATION}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{talib@eng.tau.ac.il}},
Funding-Acknowledgement = {{Israel Science Foundation {[}1556/10, 930/12]; European Community
   {[}PIRG05-GA-2009-248527]}},
Funding-Text = {{This work was supported in part by Israel Science Foundation Grant No.
   1556/10 and 930/12, and European Community Grant PIRG05-GA-2009-248527.}},
Cited-References = {{Sand P, 2004, ACM T GRAPHIC, V23, P592, DOI 10.1145/1015706.1015765.
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Number-of-Cited-References = {{33}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Int. J. Comput. Vis.}},
Doc-Delivery-Number = {{AT2HL}},
Unique-ID = {{ISI:000344754500004}},
}

@article{ ISI:000344744200012,
Author = {Li, Lin Tzy and Guimaraes Pedronette, Daniel Carlos and Almeida, Jurandy
   and Penatti, Otavio A. B. and Calumby, Rodrigo Tripodi and Torres,
   Ricardo da Silva},
Title = {{A rank aggregation framework for video multimodal geocoding}},
Journal = {{MULTIMEDIA TOOLS AND APPLICATIONS}},
Year = {{2014}},
Volume = {{73}},
Number = {{3}},
Pages = {{1323-1359}},
Month = {{DEC}},
Abstract = {{This paper proposes a rank aggregation framework for video multimodal
   geocoding. Textual and visual descriptions associated with videos are
   used to define ranked lists. These ranked lists are later combined, and
   the resulting ranked list is used to define appropriate locations for
   videos. An architecture that implements the proposed framework is
   designed. In this architecture, there are specific modules for each
   modality (e. g, textual and visual) that can be developed and evolved
   independently. Another component is a data fusion module responsible for
   combining seamlessly the ranked lists defined for each modality. We have
   validated the proposed framework in the context of the MediaEval 2012
   Placing Task, whose objective is to automatically assign geographical
   coordinates to videos. Obtained results show how our multimodal approach
   improves the geocoding results when compared to methods that rely on a
   single modality (either textual or visual descriptors). We also show
   that the proposed multimodal approach yields comparable results to the
   best submissions to the Placing Task in 2012 using no extra information
   besides the available development/training data. Another contribution of
   this work is related to the proposal of a new effectiveness evaluation
   measure. The proposed measure is based on distance scores that summarize
   how effective a designed/tested approach is, considering its overall
   result for a test dataset.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Li, LT (Reprint Author), Univ Campinas UNICAMP, Inst Comp, RECOD Lab, BR-13083852 Campinas, SP, Brazil.
   Li, Lin Tzy; Guimaraes Pedronette, Daniel Carlos; Almeida, Jurandy; Penatti, Otavio A. B.; Calumby, Rodrigo Tripodi; Torres, Ricardo da Silva, Univ Campinas UNICAMP, Inst Comp, RECOD Lab, BR-13083852 Campinas, SP, Brazil.
   Li, Lin Tzy, CPqD Fdn, Telecommun Res \& Dev Ctr, BR-13086902 Campinas, SP, Brazil.
   Guimaraes Pedronette, Daniel Carlos, Univ Estadual Paulista UNESP, Dept Stat Appl Math \& Comp, BR-13506900 Rio Claro, SP, Brazil.
   Calumby, Rodrigo Tripodi, Univ Feira Santana UEFS, Dept Exact Sci, BR-44036900 Feira De Santana, BA, Brazil.}},
DOI = {{10.1007/s11042-013-1588-4}},
ISSN = {{1380-7501}},
EISSN = {{1573-7721}},
Keywords = {{Video geotagging; Multimodal retrieval; Rank aggregation; Effectiveness
   measure}},
Keywords-Plus = {{INFORMATION-RETRIEVAL; FUSION}},
Research-Areas = {{Computer Science; Engineering}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Computer Science, Software
   Engineering; Computer Science, Theory \& Methods; Engineering,
   Electrical \& Electronic}},
Author-Email = {{lintzyli@ic.unicamp.br
   dcarlos@ic.unicamp.br
   jurandy.almeida@ic.unicamp.br
   penatti@ic.unicamp.br
   tripodi@ic.unicamp.br
   rtorres@ic.unicamp.br}},
ResearcherID-Numbers = {{Pedronette, Daniel/E-7817-2015
   }},
ORCID-Numbers = {{Torres, Ricardo/0000-0001-9772-263X}},
Funding-Acknowledgement = {{CAPES (Brazilian Federal Agency for Support and Evaluation of Graduate
   Education); FAPESP (Sao Paulo Research Foundation) {[}2011/11171-5,
   2009/10554-8]; CNPq (National Council for Scientific and Technological
   Development) {[}306580/2012-8, 484254/2012-0]; CPqD Foundation
   (Telecommunications Research and Development Center)}},
Funding-Text = {{The authors thank CAPES (Brazilian Federal Agency for Support and
   Evaluation of Graduate Education), FAPESP (Sao Paulo Research
   Foundation) grants 2011/11171-5 and 2009/10554-8, and CNPq (National
   Council for Scientific and Technological Development) grants
   306580/2012-8 and 484254/2012-0, as well as CPqD Foundation
   (Telecommunications Research and Development Center) for their support.
   Additionally we would like to thank for the suggestions and questions
   arisen by the anonymous reviewers that gave us the chance to improve our
   paper.}},
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Number-of-Cited-References = {{56}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{Multimed. Tools Appl.}},
Doc-Delivery-Number = {{AT2EH}},
Unique-ID = {{ISI:000344744200012}},
}

@article{ ISI:000344744200024,
Author = {Su, Xueping and Peng, Jinye and Feng, Xiaoyi and Wu, Jun and Fan,
   Jianping and Cui, Li},
Title = {{Cross-modality based celebrity face naming for news image collections}},
Journal = {{MULTIMEDIA TOOLS AND APPLICATIONS}},
Year = {{2014}},
Volume = {{73}},
Number = {{3}},
Pages = {{1643-1661}},
Month = {{DEC}},
Abstract = {{For automatically mining the underlying relationships between different
   famous persons in daily news, for example, building a news person based
   network with the faces as icons to facilitate face-based person finding,
   we need a tool to automatically label faces in new images with their
   real names. This paper studies the problem of linking names with faces
   from large-scale news images with captions. In our previous work, we
   proposed a method called Person-based Subset Clustering which is mainly
   based on face clustering for all face images derived from the same name.
   The location where a name appears in a caption, as well as the visual
   structural information within a news image provided informative cues
   such as who are really in the associated image. By combining the domain
   knowledge from the captions and the corresponding image we propose a
   novel cross-modality approach to further improve the performance of
   linking names with faces. The experiments are performed on the data sets
   including approximately half a million news images from Yahoo! news, and
   the results show that the proposed method achieves significant
   improvement over the clustering-only methods.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Su, XP (Reprint Author), Northwestern Polytech Univ, Sch Elect \& Informat, Xian 710072, Peoples R China.
   Su, Xueping; Peng, Jinye; Feng, Xiaoyi; Wu, Jun; Fan, Jianping; Cui, Li, Northwestern Polytech Univ, Sch Elect \& Informat, Xian 710072, Peoples R China.}},
DOI = {{10.1007/s11042-013-1578-6}},
ISSN = {{1380-7501}},
EISSN = {{1573-7721}},
Keywords = {{Affinity propagation cluster; Cross-modality; Face classification; Rank
   aggregation}},
Keywords-Plus = {{PEOPLE; NAMES}},
Research-Areas = {{Computer Science; Engineering}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Computer Science, Software
   Engineering; Computer Science, Theory \& Methods; Engineering,
   Electrical \& Electronic}},
Author-Email = {{yifeichongtian1201@163.com
   jinyepeng@nwpu.edu.cn
   fengxiao@nwpu.edu.cn
   junwu@nwpu.edu.cn
   jfan@uncc.edu
   l.cui@nwpu.edu.cn}},
Funding-Acknowledgement = {{doctorate foundation of Northwestern Polytechnical University
   {[}CX201114]; Ministry of Education Fund for Doctoral Students Newcomer
   Awards of China; National Natural Science Foundation of China
   {[}61075014, 61272285, 61103062]; Research Fund for the Doctoral Program
   of Higher Education {[}20106102110028, 20116102110027, 20116102120031,
   20126101110022]; Science and technology project of Shaanxi Province
   {[}2013K06-29]; NPU Basic Research Foundation {[}JC201249]}},
Funding-Text = {{This work is supported by the doctorate foundation of Northwestern
   Polytechnical University under CX201114, Ministry of Education Fund for
   Doctoral Students Newcomer Awards of China, National Natural Science
   Foundation of China under Grant 61075014, 61272285, 61103062, The
   Research Fund for the Doctoral Program of Higher Education under Grant
   20106102110028, 20116102110027, 20116102120031, 20126101110022, The
   Science and technology project of Shaanxi Province under Grant
   2013K06-29, and NPU Basic Research Foundation under Grant JC201249.}},
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Number-of-Cited-References = {{17}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{10}},
Journal-ISO = {{Multimed. Tools Appl.}},
Doc-Delivery-Number = {{AT2EH}},
Unique-ID = {{ISI:000344744200024}},
}

@article{ ISI:000340982800017,
Author = {Lin, Yaojin and Li, Jinjin and Lin, Menglei and Chen, Jinkun},
Title = {{A new nearest neighbor classifier via fusing neighborhood information}},
Journal = {{NEUROCOMPUTING}},
Year = {{2014}},
Volume = {{143}},
Number = {{SI}},
Pages = {{164-169}},
Month = {{NOV 2}},
Abstract = {{The nearest neighbor (NN) classification is a classical and yet
   effective technique in machine learning and data mining communities.
   However, its performance depends crucially on the distance function used
   to compute distance between samples. In this paper, we first define the
   concept of sample's neighborhood and present two related criteria
   according to neighborhood influence. Then, the influence of sample's
   neighborhood is comprehensively considered when computing the distances
   between the query and training samples. Finally, we propose an improved
   nearest neighbor classification algorithm via fusing neighborhood
   information. The proposed method can precisely characterize the distance
   among samples as well as enhance the predictive power of classifier to
   some extent. The experimental results show that the proposed algorithm
   basically outperforms classical nearest neighbor classifier and some
   other state-of-the-art classification methods. (C) 2014 Elsevier B.V.
   All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Lin, YJ (Reprint Author), Minnan Normal Univ, Sch Comp Sci, Zhangzhou 363000, Peoples R China.
   Lin, Yaojin; Li, Jinjin; Lin, Menglei, Minnan Normal Univ, Sch Comp Sci, Zhangzhou 363000, Peoples R China.
   Li, Jinjin; Chen, Jinkun, Minnan Normal Univ, Sch Math \& Stat, Zhangzhou 363000, Peoples R China.}},
DOI = {{10.1016/j.neucom.2014.06.009}},
ISSN = {{0925-2312}},
EISSN = {{1872-8286}},
Keywords = {{Nearest neighbor classifier; Neighborhood information; Distance metric;
   Rank aggregation}},
Keywords-Plus = {{PATTERN-CLASSIFICATION; ALGORITHM; DIMENSIONALITY; MODEL}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{yjlin@mail.hfut.edu.cn
   jinjinli@mnnu.edu.cn
   menglei36@126.com
   cjk99@163.com}},
Funding-Acknowledgement = {{National Natural Science Foundation of China {[}61303131, 61379021];
   Natural Science Foundation of Fujian Province {[}2013J01028, 2013J01029,
   2012D141, 2013J01265]; Department of Education of Fujian Province
   {[}JK2013027, JK2011031, JA13202, JA11171]; Science Foundation of
   Zhangzhou City {[}ZZ2013J04]}},
Funding-Text = {{This work was supported by grants from the National Natural Science
   Foundation of China (Nos. 61303131, 61379021), the Natural Science
   Foundation of Fujian Province (Nos. 2013J01028, 2013J01029, 2012D141 and
   2013J01265), the Department of Education of Fujian Province (Nos.
   JK2013027, JK2011031, JA13202 and JA11171) and the Science Foundation of
   Zhangzhou City (No. ZZ2013J04).}},
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Number-of-Cited-References = {{33}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{24}},
Journal-ISO = {{Neurocomputing}},
Doc-Delivery-Number = {{AO0EV}},
Unique-ID = {{ISI:000340982800017}},
}

@article{ ISI:000343972500011,
Author = {Wang, Hou-Ling and Chen, Jinhuan and Tian, Qianqian and Wang, Shu and
   Xia, Xinli and Yin, Weilun},
Title = {{Identification and validation of reference genes for Populus euphratica
   gene expression analysis during abiotic stresses by quantitative
   real-time PCR}},
Journal = {{PHYSIOLOGIA PLANTARUM}},
Year = {{2014}},
Volume = {{152}},
Number = {{3}},
Pages = {{529-545}},
Month = {{NOV}},
Abstract = {{Populus euphratica is the only arboreal species that is established in
   the world's largest shifting-sand desert in China and is well-adapted to
   the extreme desert environment, so it is widely considered a model
   system for researching into abiotic stress resistance of woody plants.
   However, few P. euphratica reference genes (RGs) have been identified
   for quantitative real-time polymerase chain reaction (qRT-PCR) until
   now. Validation of suitable RGs is essential for gene expression
   normalization research. In this study, we screened 16 endogenous
   candidate RGs in P. euphratica leaves in six abiotic stress treatments,
   including abscisic acid (ABA), cold, dehydration, drought,
   short-duration salt (SS) and long-duration salt (LS) treatments, each
   with 6 treatment gradients. After calculation of PCR efficiencies, three
   different software tools, NormFinder, geNorm and BestKeeper, were
   employed to analyze the qRT-PCR data systematically, and the outputs
   were merged by means of a non-weighted unsupervised rank aggregation
   method. The genes selected as optimal for gene expression analysis of
   the six treatments were RPL17 (ribosomal protein L17) in ABA, EF1
   (elongation factor-1 alpha) in cold, HIS (histone superfamily protein
   H3) in dehydration, GII in drought and SS, and TUB (tubulin) in LS. The
   expression of 60S (the 60S ribosomal protein) varied the least during
   all treatments. To illustrate the suitability of these RGs, the relative
   quantifications of three stress-inducible genes, PePYL1, PeSCOF-1 and
   PeSCL7 were investigated with different RGs. The results, calculated
   using qBasePlus software, showed that compared with the
   least-appropriate RGs, the expression profiles normalized by the
   recommended RGs were closer to expectations. Our study provided an
   important RG application guideline for P. euphratica gene expression
   characterization.}},
Publisher = {{WILEY-BLACKWELL}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Xia, XL (Reprint Author), Beijing Forestry Univ, Coll Biol Sci \& Technol, Natl Engn Lab Tree Breeding, Beijing 100083, Peoples R China.
   Wang, Hou-Ling; Chen, Jinhuan; Tian, Qianqian; Wang, Shu; Xia, Xinli; Yin, Weilun, Beijing Forestry Univ, Coll Biol Sci \& Technol, Natl Engn Lab Tree Breeding, Beijing 100083, Peoples R China.
   Wang, Hou-Ling; Yin, Weilun, Beijing Forestry Univ, Coll Forestry, Key Lab Silviculture \& Conservat, Beijing 100083, Peoples R China.}},
DOI = {{10.1111/ppl.12206}},
ISSN = {{0031-9317}},
EISSN = {{1399-3054}},
Keywords-Plus = {{POLYMERASE-CHAIN-REACTION; RT-PCR; INTERNAL CONTROL; RELATIVE
   QUANTIFICATION; ACCURATE NORMALIZATION; HOUSEKEEPING GENES; DROUGHT
   TOLERANCE; COLD TOLERANCE; SELECTION; PROTEIN}},
Research-Areas = {{Plant Sciences}},
Web-of-Science-Categories  = {{Plant Sciences}},
Author-Email = {{xiaxl@bjfu.edu.cn
   yinwl@bjfu.edu.cn}},
Funding-Acknowledgement = {{Hi-Tech Research and Development Program of China {[}2013AA102701];
   National Natural Science Foundation of China {[}31270656]; BMEC; Beijing
   Forestry University {[}B13007]}},
Funding-Text = {{We would like to thank Jing Hu (University of Alabama, Birmingham, USA)
   for providing us the QBASE software and some practical guidances; and
   Sha Tang, Xian Wu, Peng Shuai, Tao Pang, Xiao Han, Wei Han and Chao Yuan
   for their help and insightful comments on the experiments. This work was
   supported by the Hi-Tech Research and Development Program of China
   (2013AA102701), the National Natural Science Foundation of China
   (31270656), Joint Programs of the Scientific Research and Graduate
   Training from BMEC (Stress Resistance Mechanism of Poplar) and 111
   Project of Beijing Forestry University (B13007).}},
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Number-of-Cited-References = {{55}},
Times-Cited = {{10}},
Usage-Count-(Last-180-days) = {{15}},
Usage-Count-Since-2013 = {{67}},
Journal-ISO = {{Physiol. Plant.}},
Doc-Delivery-Number = {{AS0MY}},
Unique-ID = {{ISI:000343972500011}},
}

@article{ ISI:000343662800105,
Author = {Borges, Alexandre Filipe and Fonseca, Catarina and Ferreira, Ricardo
   Boavida and Lourenco, Ana Maria and Monteiro, Sara},
Title = {{Reference Gene Validation for Quantitative RT-PCR during Biotic and
   Abiotic Stresses in Vitis vinifera}},
Journal = {{PLOS ONE}},
Year = {{2014}},
Volume = {{9}},
Number = {{10}},
Month = {{OCT 23}},
Abstract = {{Grapevine is one of the most cultivated fruit crop worldwide with Vitis
   vinifera being the species with the highest economical importance. Being
   highly susceptible to fungal pathogens and increasingly affected by
   environmental factors, it has become an important agricultural research
   area, where gene expression analysis plays a fundamental role.
   Quantitative reverse transcription polymerase chain reaction (qRT-PCR)
   is currently amongst the most powerful techniques to perform gene
   expression studies. Nevertheless, accurate gene expression
   quantification strongly relies on appropriate reference gene selection
   for sample normalization. Concerning V. vinifera, limited information
   still exists as for which genes are the most suitable to be used as
   reference under particular experimental conditions. In this work, seven
   candidate genes were investigated for their stability in grapevine
   samples referring to four distinct stresses (Erysiphe necator, wounding
   and UV-C irradiation in leaves and Phaeomoniella chlamydospora
   colonization in wood). The expression stability was evaluated using
   geNorm, NormFinder and BestKeeper. In all cases, full agreement was not
   observed for the three methods. To provide comprehensive rankings
   integrating the three different programs, for each treatment, a
   consensus ranking was created using a non-weighted unsupervised rank
   aggregation method. According to the last, the three most suitable
   reference genes to be used in grapevine leaves, regardless of the
   stress, are UBC, VAG and PEP. For the P. chlamydospora treatment, EF1,
   CYP and UBC were the best scoring genes. Acquaintance of the most
   suitable reference genes to be used in grapevine samples can contribute
   for accurate gene expression quantification in forthcoming studies.}},
Publisher = {{PUBLIC LIBRARY SCIENCE}},
Address = {{1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Borges, AF (Reprint Author), Univ Nova Lisboa, Inst Tecnol Quim \& Biol, Dis \& Stress Biol Lab, Oeiras, Portugal.
   Borges, Alexandre Filipe; Ferreira, Ricardo Boavida, Univ Nova Lisboa, Inst Tecnol Quim \& Biol, Dis \& Stress Biol Lab, Oeiras, Portugal.
   Borges, Alexandre Filipe; Fonseca, Catarina; Ferreira, Ricardo Boavida; Monteiro, Sara, Univ Lisbon, Dis \& Stress Biol Lab, Inst Super Agron, P-1699 Lisbon, Portugal.
   Lourenco, Ana Maria, Univ Nova Lisboa, Fac Ciencias \& Tecnol, REQUIMTE, Dept Quim, Caparica, Portugal.}},
DOI = {{10.1371/journal.pone.0111399}},
Article-Number = {{e111399}},
ISSN = {{1932-6203}},
Keywords-Plus = {{REAL-TIME PCR; POLYMERASE-CHAIN-REACTION; EXPRESSION ANALYSIS;
   HOUSEKEEPING GENES; INTERNAL CONTROL; GRAPEVINE; NORMALIZATION;
   SELECTION; PATHOGEN; IDENTIFICATION}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{afgborges@isa.utl.pt}},
ResearcherID-Numbers = {{Lourenco, Ana/C-9024-2013
   }},
ORCID-Numbers = {{Borges, Alexandre/0000-0002-8130-764X
   Lourenco, Ana/0000-0001-7358-3428
   Monteiro, Sara/0000-0002-7069-0591}},
Funding-Acknowledgement = {{Fundacao para a Ciencia e a Tecnologia {[}PTDC/AGR PRO/112340/2009,
   SFRH/BD/61903/2009]}},
Funding-Text = {{Financial support was provided by Project PTDC/AGR PRO/112340/2009 from
   Fundacao para a Ciencia e a Tecnologia
   (http://www.fct.pt/index.phtml.en). AFB was supported by Fundacao para a
   Ciencia e a Tecnologia, PhD grant SFRH/BD/61903/2009. The funders had no
   role in study design, data collection and analysis, decision to publish,
   or preparation of the manuscript.}},
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Number-of-Cited-References = {{51}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{24}},
Journal-ISO = {{PLoS One}},
Doc-Delivery-Number = {{AR5ZY}},
Unique-ID = {{ISI:000343662800105}},
}

@article{ ISI:000343210300034,
Author = {Vanhauwaert, Suzanne and Van Peer, Gert and Rihani, Ali and Janssens,
   Els and Rondou, Pieter and Lefever, Steve and De Paepe, Anne and Coucke,
   Paul J. and Speleman, Frank and Vandesompele, Jo and Willaert, Andy},
Title = {{Expressed Repeat Elements Improve RT-qPCR Normalization across a Wide
   Range of Zebrafish Gene Expression Studies}},
Journal = {{PLOS ONE}},
Year = {{2014}},
Volume = {{9}},
Number = {{10}},
Month = {{OCT 13}},
Abstract = {{The selection and validation of stably expressed reference genes is a
   critical issue for proper RT-qPCR data normalization. In zebrafish
   expression studies, many commonly used reference genes are not generally
   applicable given their variability in expression levels under a variety
   of experimental conditions. Inappropriate use of these reference genes
   may lead to false interpretation of expression data and unreliable
   conclusions. In this study, we evaluated a novel normalization method in
   zebrafish using expressed repetitive elements (ERE) as reference
   targets, instead of specific protein coding mRNA targets. We assessed
   and compared the expression stability of a number of EREs to that of
   commonly used zebrafish reference genes in a diverse set of experimental
   conditions including a developmental time series, a set of different
   organs from adult fish and different treatments of zebrafish embryos
   including morpholino injections and administration of chemicals. Using
   geNorm and rank aggregation analysis we demonstrated that EREs have a
   higher overall expression stability compared to the commonly used
   reference genes. Moreover, we propose a limited set of ERE reference
   targets (hatn10, dna15ta1 and loopern4), that show stable expression
   throughout the wide range of experiments in this study, as strong
   candidates for inclusion as reference targets for qPCR normalization in
   future zebrafish expression studies. Our applied strategy to find and
   evaluate candidate expressed repeat elements for RT-qPCR data
   normalization has high potential to be used also for other species.}},
Publisher = {{PUBLIC LIBRARY SCIENCE}},
Address = {{1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Willaert, A (Reprint Author), Univ Ghent, Ctr Med Genet, B-9000 Ghent, Belgium.
   Vanhauwaert, Suzanne; Van Peer, Gert; Rihani, Ali; Janssens, Els; Rondou, Pieter; Lefever, Steve; De Paepe, Anne; Coucke, Paul J.; Speleman, Frank; Vandesompele, Jo; Willaert, Andy, Univ Ghent, Ctr Med Genet, B-9000 Ghent, Belgium.}},
DOI = {{10.1371/journal.pone.0109091}},
Article-Number = {{e109091}},
ISSN = {{1932-6203}},
Keywords-Plus = {{REAL-TIME PCR; POLYMERASE-CHAIN-REACTION; HOUSEKEEPING GENES;
   RIBOSOMAL-RNA; MESSENGER; QUANTIFICATION; VALIDATION; INAPPROPRIATE;
   EMBRYOS; GLUT10}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{andy.willaert@ugent.be}},
Funding-Acknowledgement = {{Ghent University {[}BOF08/01M01108]; GOA-UGent grant {[}12051203]; Fund
   for Scientific Research - Flanders (FWO) {[}G.0574.13]; Belgian Program
   of Interuniversity Poles of Attraction IUAP; Stichting tegen kanker
   {[}365O9110]; Fund for Scientific Research - Flanders (FWO); Ghent
   University research fund (BOF); Fund for Scientific Research Flanders
   (FWO); Special Research Fund (BOF) of Ghent University}},
Funding-Text = {{This work was supported by Ghent University (Methusalem grant
   BOF08/01M01108 to A. D. P., GOA-UGent grant no. 12051203 to F. S.), by
   the Fund for Scientific Research - Flanders (FWO) (grant no. G.0574.13
   to P. C.), by the Belgian Program of Interuniversity Poles of Attraction
   IUAP (to F. S.) and by the ``Stichting tegen kanker'' (grant no.
   365O9110 to F. S.). S. V. is supported by a PhD fellowship from the Fund
   for Scientific Research - Flanders (FWO). G. V. P. and A. R. are
   supported by a PhD fellowship from the Ghent University research fund
   (BOF). P. R. has a postdoctoral research grant from the Fund for
   Scientific Research Flanders (FWO). A. W. and S. L. are postdoctoral
   fellows supported by the Special Research Fund (BOF) of Ghent
   University. The funders had no role in study design, data collection and
   analysis, decision to publish, or preparation of the manuscript.}},
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Number-of-Cited-References = {{44}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{12}},
Journal-ISO = {{PLoS One}},
Doc-Delivery-Number = {{AQ9WZ}},
Unique-ID = {{ISI:000343210300034}},
}

@article{ ISI:000342416900036,
Author = {Farnoud (Hassanzadeh), Farzad and Milenkovic, Olgica},
Title = {{An Axiomatic Approach to Constructing Distances for Rank Comparison and
   Aggregation}},
Journal = {{IEEE TRANSACTIONS ON INFORMATION THEORY}},
Year = {{2014}},
Volume = {{60}},
Number = {{10}},
Pages = {{6417-6439}},
Month = {{OCT}},
Abstract = {{We propose a new family of distance measures on rankings, derived
   through an axiomatic approach, that consider the nonuniform relevance of
   the top and bottom of ordered lists and similarities between candidates.
   The proposed distance functions include specialized weighted versions of
   the Kendall tau distance and the Cayley distance, and are suitable for
   comparing rankings in a number of applications, including information
   retrieval and rank aggregation. In addition to proposing the distance
   measures and providing the theoretical underpinnings for their
   applications, we also analyze algorithmic and computational aspects of
   weighted distance-based rank aggregation. We present an aggregation
   method based on approximating weighted distance measures by a
   generalized version of Spearman's footrule distance as well as a Markov
   chain method inspired by PageRank, where transition probabilities of the
   Markov chain reflect the chosen weighted distances.}},
Publisher = {{IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC}},
Address = {{445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Farnoud, F (Reprint Author), CALTECH, Dept Elect Engn, Pasadena, CA 91125 USA.
   Farnoud (Hassanzadeh), Farzad; Milenkovic, Olgica, Univ Illinois, Dept Elect \& Comp Engn, Urbana, IL 61801 USA.}},
DOI = {{10.1109/TIT.2014.2345760}},
ISSN = {{0018-9448}},
EISSN = {{1557-9654}},
Keywords = {{Weighted Kendall distance; positional relevance; top-vs-bottom;
   similarity; rank aggregation; information retrieval; statistics;
   collaborative filtering; PageRank}},
Keywords-Plus = {{KENDALLS TAU; CODES}},
Research-Areas = {{Computer Science; Engineering}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Engineering, Electrical \&
   Electronic}},
Author-Email = {{farnoud@caltech.edu
   milenkov@illinois.edu}},
Funding-Acknowledgement = {{National Science Foundation {[}CCF-0821910, CCF-0809895]; Emerging
   Frontiers for Science of Information Center {[}CCF 0939370]; Air Force
   Office of Scientific Research Complex Networks Grant}},
Funding-Text = {{This work was supported in part by the National Science Foundation under
   Grant CCF-0821910 and Grant CCF-0809895, in part by the Emerging
   Frontiers for Science of Information Center under Grant CCF 0939370, and
   in part by an Air Force Office of Scientific Research Complex Networks
   Grant. This paper was presented at the 2012 International Conference on
   Signal Processing and Communications, 2012 Annual International
   Conference on Information Theory and Applications, and 2013 IEEE
   Information Theory and Workshop.}},
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Number-of-Cited-References = {{43}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{IEEE Trans. Inf. Theory}},
Doc-Delivery-Number = {{AP9RH}},
Unique-ID = {{ISI:000342416900036}},
}

@article{ ISI:000336440400001,
Author = {Betzler, Nadja and Bredereck, Robert and Niedermeier, Rolf},
Title = {{Theoretical and empirical evaluation of data reduction for exact Kemeny
   Rank Aggregation}},
Journal = {{AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS}},
Year = {{2014}},
Volume = {{28}},
Number = {{5}},
Pages = {{721-748}},
Month = {{SEP}},
Abstract = {{Kemeny Rank Aggregation is a consensus finding problem important in many
   areas ranging from classical voting over web search and databases to
   bioinformatics. The underlying decision problem Kemeny Score is
   NP-complete even in case of four input rankings to be aggregated into a
   ``median ranking{''}. We analyze efficient polynomial-time data
   reduction rules with provable performance bounds that allow us to find
   even all optimal median rankings. We show that our reduced instances
   contain at most candidates where denotes the average Kendall's tau
   distance between the input votes. On the theoretical side, this improves
   a corresponding result for a ``partial problem kernel{''} from quadratic
   to linear size. In this context we provide a theoretical analysis of a
   commonly used data reduction. On the practical side, we provide
   experimental results with data based on web search and sport
   competitions, e.g., computing optimal median rankings for real-world
   instances with more than 100 candidates within milliseconds. Moreover,
   we perform experiments with randomly generated data based on two random
   distribution models for permutations.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Bredereck, R (Reprint Author), TU Berlin, Inst Softwaretech \& Theoret Informat, Berlin, Germany.
   Betzler, Nadja; Bredereck, Robert; Niedermeier, Rolf, TU Berlin, Inst Softwaretech \& Theoret Informat, Berlin, Germany.}},
DOI = {{10.1007/s10458-013-9236-y}},
ISSN = {{1387-2532}},
EISSN = {{1573-7454}},
Keywords = {{Kemeny score; NP-hardness; Parameterized algorithmics; Preprocessing;
   Average parameterization; Partial problem kernel; Experiments}},
Keywords-Plus = {{ALGORITHMS; PERMUTATIONS; COMPLEXITY; ELECTION; MODELS}},
Research-Areas = {{Automation \& Control Systems; Computer Science}},
Web-of-Science-Categories  = {{Automation \& Control Systems; Computer Science, Artificial Intelligence}},
Author-Email = {{robert.bredereck@tu-berlin.de
   rolf.niedermeier@tu-berlin.de}},
Funding-Acknowledgement = {{DFG {[}NI 369/10]}},
Funding-Text = {{We are grateful to the anonymous referees of the Fifth International
   Symposium on Parameterized and Exact Computation (IPEC-2010) and of the
   Third International Workshop on Computational Social Choice
   (COMSOC-2010) for constructive feedback helping to improve this work. We
   are indebted to three anonymous referees of JAAMAS for providing
   numerous insightful remarks that helped to significantly improve the
   paper. In particular, the more efficient and effective data reduction
   rule exploiting the extended Condorcet property helped to improve our
   theoretical and practical results. We thank Christian Komusiewicz for
   pointing us to an improved (compared to the conference version) analysis
   for the bound of Theorem 1, and our student research assistant Leila
   Arras for her great support in doing implementations and experiments
   with synthetic data. Nadja Betzler and Robert Bredereck were supported
   by the DFG, research project PAWS, NI 369/10.}},
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Number-of-Cited-References = {{41}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Auton. Agents Multi-Agent Syst.}},
Doc-Delivery-Number = {{AH9DD}},
Unique-ID = {{ISI:000336440400001}},
}

@article{ ISI:000340413900015,
Author = {Hirsch, Jan D. and Metz, Kelli R. and Hosokawa, Patrick W. and Libby,
   Anne M.},
Title = {{Validation of a Patient-Level Medication Regimen Complexity Index as a
   Possible Tool to Identify Patients for Medication Therapy Management
   Intervention}},
Journal = {{PHARMACOTHERAPY}},
Year = {{2014}},
Volume = {{34}},
Number = {{8}},
Pages = {{826-835}},
Month = {{AUG}},
Abstract = {{BACKGROUND The Medication Regimen Complexity Index (MRCI) is a 65-item
   instrument that can be used to quantify medication regimen complexity at
   the patient level, capturing all prescribed and over-the-counter
   medications. Although the MRCI has been used in several studies, the
   narrow scope of the initial validation limits application at a
   population or clinical practice level.
   PURPOSE To conduct a MRCI validation pertinent to the desired clinical
   use to identify patients for medication therapy management
   interventions.
   METHODS An expert panel of clinical pharmacists ranked medication
   regimen complexity for two samples of cases: a single-disease cohort
   (diabetes mellitus) and a multiple-disease cohort (diabetes mellitus,
   hypertension, human immunodeficiency virus infection, geriatric
   depression). Cases for expert panel review were selected from 400
   ambulatory clinic patients, and each case description included data that
   were available via claims or electronic medical records (EMRs).
   Construct validity was assessed using patient-level MRCI scores,
   medication count, and additional patient data. Concordance was evaluated
   using weighted kappa agreement statistic, and correlations were
   determined using Spearman rank-order correlation coefficient (rho) or
   Kendall tau.
   RESULTS Moderate to good concordance between patient-level MRCI scores
   and expert medication regimen complexity ranking was observed (claims
   data, consensus ranking: single-disease cohort 0.55, multiple disease
   cohort 0.63). In contrast, only fair to moderate concordance was
   observed for medication count (single-disease cohort 0.33,
   multiple-disease cohort 0.48). Adding more-detailed administration
   directions from EMR data did not improve concordance. MRCI convergent
   validity was supported by strong correlations with medication count (all
   cohorts 0.90) and moderate correlations with morbidity measures (e.g.,
   all cohorts; number of comorbidities 0.46, Chronic Disease Score 0.46).
   Nonsignificant correlation of MRCI scores with age and gender (all
   cohorts 0.08 and 0.06, respectively) supported MRCI divergent validity.
   LIMITATIONS This study used cross-sectional, retrospective patient data
   for a small number of patients and clinical pharmacists from only two
   universities; therefore, results may have limited generalizability.
   CONCLUSIONS The patient-level MRCI is a valid tool for assessing
   medication regimen complexity that can be applied by using data commonly
   found in claims and EMR databases and could be useful to identify
   patients who may benefit from medication therapy management.}},
Publisher = {{WILEY-BLACKWELL}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Hirsch, JD (Reprint Author), 9500 Gilman Dr MC 0714, La Jolla, CA 92093 USA.
   Hirsch, Jan D., Univ Calif San Diego, Skaggs Sch Pharm \& Pharmaceut Sci, La Jolla, CA 92093 USA.
   Hirsch, Jan D., Vet Affairs San Diego Healthcare Syst, San Diego, CA USA.
   Metz, Kelli R.; Libby, Anne M., Univ Colorado, Skaggs Sch Pharm \& Pharmaceut Sci, Dept Clin Pharm, Aurora, CO USA.
   Hosokawa, Patrick W.; Libby, Anne M., Univ Colorado, Sch Med, Colorado Hlth Outcomes Program, Aurora, CO USA.}},
DOI = {{10.1002/phar.1452}},
ISSN = {{0277-0008}},
EISSN = {{1875-9114}},
Keywords = {{medication regimen complexity; MRCI; complexity; medication therapy
   management; MTM; geriatrics; hypertension; diabetes; human
   immunodeficiency virus; HIV; chronic disease}},
Keywords-Plus = {{QUALITY-OF-LIFE; CARE}},
Research-Areas = {{Pharmacology \& Pharmacy}},
Web-of-Science-Categories  = {{Pharmacology \& Pharmacy}},
Author-Email = {{janhirsch@ucsd.edu}},
ResearcherID-Numbers = {{Libby, Anne/B-6984-2013}},
Funding-Acknowledgement = {{ALSAM Foundation Skaggs Scholars Program grant at the University of
   Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences;
   University of California San Diego Skaggs School of Pharmacy and
   Pharmaceutical Sciences}},
Funding-Text = {{This study was funded by the ALSAM Foundation Skaggs Scholars Program
   grant at the University of Colorado Skaggs School of Pharmacy and
   Pharmaceutical Sciences (Dr. Libby) and the University of California San
   Diego Skaggs School of Pharmacy and Pharmaceutical Sciences (Dr.
   Hirsch).}},
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Number-of-Cited-References = {{24}},
Times-Cited = {{7}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{Pharmacotherapy}},
Doc-Delivery-Number = {{AN2KL}},
Unique-ID = {{ISI:000340413900015}},
}

@article{ ISI:000342852100019,
Author = {Deng, Ke and Han, Simeng and Li, Kate J. and Liu, Jun S.},
Title = {{Bayesian Aggregation of Order-Based Rank Data}},
Journal = {{JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION}},
Year = {{2014}},
Volume = {{109}},
Number = {{507}},
Pages = {{1023-1039}},
Month = {{JUL 3}},
Abstract = {{Rank aggregation, that is, combining several ranking functions (called
   base rankers) to get aggregated, usually stronger rankings of a given
   set of items, is encountered in many disciplines. Most methods in the
   literature assume that base rankers of interest are equally reliable. It
   is very common in practice, however, that some rankers are more
   informative and reliable than others. It is desirable to distinguish
   high quality base rankers from low quality ones and treat them
   differently. Some methods achieve this by assigning prespecified weights
   to base rankers. But there are no systematic and principled strategies
   for designing a proper weighting scheme for a practical problem. In this
   article, we propose a Bayesian approach, called Bayesian aggregation of
   rank data (BARD), to overcome this limitation. By attaching a quality
   parameter to each base ranker and estimating these parameters along with
   the aggregation process, BARD measures reliabilities of base rankers in
   a quantitative way and makes use of this information to improve the
   aggregated ranking. In addition, we design a method to detect highly
   correlated rankers and to account for their information redundancy
   appropriately. Both simulation studies and real data applications show
   that BARD significantly outperforms existing methods when equality of
   base rankers varies greatly.}},
Publisher = {{AMER STATISTICAL ASSOC}},
Address = {{732 N WASHINGTON ST, ALEXANDRIA, VA 22314-1943 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Deng, K (Reprint Author), Tsinghua Univ, Ctr Math Sci, Beijing 100084, Peoples R China.
   Deng, Ke, Tsinghua Univ, Ctr Math Sci, Beijing 100084, Peoples R China.
   Han, Simeng; Liu, Jun S., Harvard Univ, Dept Stat, Cambridge, MA 02138 USA.
   Li, Kate J., Suffolk Univ, Sawyer Business Sch, Boston, MA 02108 USA.}},
DOI = {{10.1080/01621459.2013.878660}},
ISSN = {{0162-1459}},
EISSN = {{1537-274X}},
Keywords = {{Power law distribution; Spam detection; Meta-analysis; Rank aggregation}},
Keywords-Plus = {{PROSTATE-CANCER; MODELS; LISTS}},
Research-Areas = {{Mathematics}},
Web-of-Science-Categories  = {{Statistics \& Probability}},
Author-Email = {{kdeng@math.tsinghua.edu.cn
   han@fas.harvard.edu
   kjli@suffolk.edu
   jliu@stat.harvard.edu}},
Funding-Acknowledgement = {{NSF {[}DMS-0706989, DMS-1007762, DMS-1208771]; Shenzhen Special Fund for
   Strategic Emerging Industry grant {[}ZD201111080127A]}},
Funding-Text = {{This research was supported in part by the NSF grants DMS-0706989,
   DMS-1007762 and DMS-1208771, and by Shenzhen Special Fund for Strategic
   Emerging Industry grant (No.ZD201111080127A).}},
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Number-of-Cited-References = {{36}},
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Journal-ISO = {{J. Am. Stat. Assoc.}},
Doc-Delivery-Number = {{AQ5MA}},
Unique-ID = {{ISI:000342852100019}},
}

@article{ ISI:000340101400024,
Author = {Huang, Keman and Fan, Yushun and Tan, Wei},
Title = {{Recommendation in an Evolving Service Ecosystem Based on Network
   Prediction}},
Journal = {{IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING}},
Year = {{2014}},
Volume = {{11}},
Number = {{3}},
Pages = {{906-920}},
Month = {{JUL}},
Abstract = {{Service computing plays a critical role in business automation and we
   can observe a rapid increase of web services and their compositions
   nowadays. Web services, their compositions, providers, consumers, and
   other entities such as context information, collectively form an
   evolving service ecosystem. Many service recommendation methods have
   been proposed to facilitate the use of services. However, existing
   approaches are mostly based on all-time statistics of usage patterns,
   and overlook the temporal aspect, i.e., the evolution of the ecosystem.
   As a result, recommendation may consist of obsolete services and also
   does not reflect the latest trend in the ecosystem. In order to overcome
   this limitation, we propose an innovative three-phase network prediction
   approach (NPA) for evolution-aware recommendation. First, we introduce a
   network series model to formalize the evolution of the service ecosystem
   and then develop a network analysis method to study the usage pattern
   with a special focus on its temporal evolution. Afterward a novel
   service network prediction method based on rank aggregation is proposed
   to predict the evolution of the network. Finally, using the network
   prediction model, we present how to recommend potential compositions,
   top services and service chains, respectively. Experiments on the
   real-world ProgrammableWeb data set show that our method achieves a
   superior performance in service recommendation, compared with those that
   are agnostic to the evolution of a service ecosystem.
   Note to Practitioners-Understanding the usage pattern and the evolution
   mechanism can help better recommend services and their compositions to
   developers. Our hypotheses are: 1) historical information carries the
   usage patterns and evolution mechanism of the ecosystem and 2) services
   are not isolated but collaborative with each other, therefore, we should
   not only concern about individual services but also their correlations.
   Based on these hypotheses, our network prediction-based approach
   constructs the network series model based on historical information, and
   transform the evolution prediction into a network prediction problem.
   Furthermore, we predict the future behavior of the network based on link
   prediction. Based on the predicted network, we recommend potential
   compositions, services, and service chains that are evolution-aware and
   better reflect the up-to-date trend in the ecosystem.}},
Publisher = {{IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC}},
Address = {{445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Fan, YS (Reprint Author), Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China.
   Huang, Keman; Fan, Yushun, Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China.
   Tan, Wei, IBM TJ Watson Res Ctr, Yorktown Hts, NY 10598 USA.}},
DOI = {{10.1109/TASE.2013.2297026}},
ISSN = {{1545-5955}},
EISSN = {{1558-3783}},
Keywords = {{Evolving service ecosystem; link prediction; network analysis;
   network-based recommendation; network series model; rank aggregation}},
Keywords-Plus = {{COMPLEX NETWORKS; MASHUP ECOSYSTEM; WEB}},
Research-Areas = {{Automation \& Control Systems}},
Web-of-Science-Categories  = {{Automation \& Control Systems}},
Author-Email = {{victoryhkm@gmail.com
   fanyus@ts-inghua.edu.cn
   wtan@us.ibm.com}},
Funding-Acknowledgement = {{National Natural Science Foundation of China {[}61174169]; National Key
   Technology RD Program {[}2012BAF15G01]}},
Funding-Text = {{This paper was recommended for publication by Associate Editor B.
   Turchiano and Editor H. Ding upon evaluation of the reviewers' comments.
   This work was supported in part by the National Natural Science
   Foundation of China (61174169) and the National Key Technology R\&D
   Program (2012BAF15G01). (Corresponding author: Y. Fan.)}},
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Number-of-Cited-References = {{50}},
Times-Cited = {{8}},
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Usage-Count-Since-2013 = {{13}},
Journal-ISO = {{IEEE Trans. Autom. Sci. Eng.}},
Doc-Delivery-Number = {{AM8DS}},
Unique-ID = {{ISI:000340101400024}},
}

@article{ ISI:000336016400033,
Author = {Muravyov, Sergey V.},
Title = {{Dealing with chaotic results of Kemeny ranking determination}},
Journal = {{MEASUREMENT}},
Year = {{2014}},
Volume = {{51}},
Pages = {{328-334}},
Month = {{MAY}},
Abstract = {{Multidimensional ordinal measurement in a form of problem of a single
   consensus ranking determination for m rankings of n alternatives is
   considered in the paper. The Kemeny rule is one of deeply justified ways
   to solve the problem allowing to find such a linear order (Kemeny
   ranking) of alternatives that a distance (defined in terms of a number
   of pair-wise disagreements between rankings) from it to the initial
   rankings is minimal. But computational experiments outcomes show that
   the approach can give considerably more than one optimal solutions what
   argues instability of the measurement procedure. Hence, special efforts
   to avoid this phenomenon are needed. (C) 2014 Elsevier Ltd. All rights
   reserved.}},
Publisher = {{ELSEVIER SCI LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Muravyov, SV (Reprint Author), Natl Res Tomsk Polytech Univ, Dept Comp Aided Measurement Syst \& Metrol, Pr Lenina 30, Tomsk 634050, Russia.
   Natl Res Tomsk Polytech Univ, Dept Comp Aided Measurement Syst \& Metrol, Tomsk 634050, Russia.}},
DOI = {{10.1016/j.measurement.2014.02.027}},
ISSN = {{0263-2241}},
EISSN = {{1873-412X}},
Keywords = {{Multidimensional ordinal measurement; Consensus relation; Kemeny ranking
   problem; Multiple optimal solutions}},
Keywords-Plus = {{PROBABILITY; CYCLES}},
Research-Areas = {{Engineering; Instruments \& Instrumentation}},
Web-of-Science-Categories  = {{Engineering, Multidisciplinary; Instruments \& Instrumentation}},
Author-Email = {{muravyov@camsam.tpu.ru}},
ResearcherID-Numbers = {{Muravyov, Sergey/N-2896-2013}},
ORCID-Numbers = {{Muravyov, Sergey/0000-0001-5650-1400}},
Funding-Acknowledgement = {{Ministry of Education and Science of Russian Federation {[}2078]}},
Funding-Text = {{The author would like to thank his Master student Asel Sukhanova and
   also exchange students Morgane Mazur and Mathilde Gharras (University of
   Angers, France) for their indispensible help in the computing
   experiments implementation. This work was partly supported by the
   Ministry of Education and Science of Russian Federation, Project \#
   2078.}},
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   Richards D., 1998, BULLETIN, P98.
   Roberts F. S., 1979, MEASUREMENT THEORY A.
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   Van Deemen A, 1999, SOC CHOICE WELFARE, V16, P171, DOI 10.1007/s003550050138.}},
Number-of-Cited-References = {{19}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Measurement}},
Doc-Delivery-Number = {{AH3IH}},
Unique-ID = {{ISI:000336016400033}},
}

@article{ ISI:000334277800017,
Author = {Garcia, J. A. and Rodriguez-Sanchez, Rosa and Fdez-Valdivia, J. and de
   Moya-Anegon, F.},
Title = {{A web application for aggregating conflicting reviewers' preferences}},
Journal = {{SCIENTOMETRICS}},
Year = {{2014}},
Volume = {{99}},
Number = {{2}},
Pages = {{523-539}},
Month = {{MAY}},
Abstract = {{Drawing on social choice theory we derive a rationale in which each
   reviewer is asked to provide his or her second, third, and fourth choice
   in addition to his/her first choice recommendation regarding the
   acceptance/revision/rejection of a given manuscript. All reviewers'
   hierarchies of alternatives are collected and combined such that an
   overall ranking can be computed. Consequently, conflicting
   recommendations are resolved not by asking a third adjudicating reviewer
   for his/her recommendation as is usual editorial praxis in many
   scientific journals, but rather by using more information from the
   available judges. After a brief introduction into social choice theory
   and a description and justification of the maximum likelihood rule for
   ranking alternatives, we describe and demonstrate a public available web
   application that provides easy-to-use tools to apply these methods for
   aggregating conflicting reviewers' recommendations. This application
   might be accessed by editors to aid their decision process in case they
   receive conflicting recommendations by their reviewers.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Garcia, JA (Reprint Author), Univ Granada, CITIC UGR, Dept Ciencias Computac \& IA, E-18071 Granada, Spain.
   Garcia, J. A.; Rodriguez-Sanchez, Rosa; Fdez-Valdivia, J., Univ Granada, CITIC UGR, Dept Ciencias Computac \& IA, E-18071 Granada, Spain.
   de Moya-Anegon, F., CSIC, CCHS, Inst Polit \& Bienes Publ IPP, Madrid 28037, Spain.}},
DOI = {{10.1007/s11192-013-1198-y}},
ISSN = {{0138-9130}},
EISSN = {{1588-2861}},
Keywords = {{Peer review; Conflicting recommendations; Social choice theory; Ranking
   rule; Consensus ranking}},
Keywords-Plus = {{STANDS TODAY; JOURNALS}},
Research-Areas = {{Computer Science; Information Science \& Library Science}},
Web-of-Science-Categories  = {{Computer Science, Interdisciplinary Applications; Information Science \&
   Library Science}},
Author-Email = {{jags@decsai.ugr.es}},
ResearcherID-Numbers = {{Garcia, Jose /C-1703-2010
   Moya Anegon, Felix/C-4004-2009
   }},
ORCID-Numbers = {{Garcia, Jose /0000-0001-7742-7270
   Moya Anegon, Felix/0000-0002-0255-8628
   Rodriguez Sanchez, Rosa Maria/0000-0001-7886-9329}},
Funding-Acknowledgement = {{Spanish Board for Science and Technology (MICINN) {[}TIN2010-15157];
   European FEDER funds}},
Funding-Text = {{This research was sponsored by the Spanish Board for Science and
   Technology (MICINN) under grant TIN2010-15157 cofinanced with European
   FEDER funds. Sincere thanks are due to the reviewers for their
   insightful comments, constructive suggestions, and help.}},
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Number-of-Cited-References = {{19}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{19}},
Journal-ISO = {{Scientometrics}},
Doc-Delivery-Number = {{AE8UJ}},
Unique-ID = {{ISI:000334277800017}},
}

@article{ ISI:000333775900051,
Author = {Theussl, Stefan and Reutterer, Thomas and Hornik, Kurt},
Title = {{How to derive consensus among various marketing journal rankings?}},
Journal = {{JOURNAL OF BUSINESS RESEARCH}},
Year = {{2014}},
Volume = {{67}},
Number = {{5}},
Pages = {{998-1006}},
Month = {{MAY}},
Abstract = {{Despite the increasing popularity of journal rankings to evaluate the
   quality of research contributions, the individual rankings for journals
   that ranked below the top tier of publications usually feature only
   modest agreement. Attempts to merge rankings into meta-rankings suffer
   from some methodological issues, such as mixed measurement scales and
   incomplete data. This paper addresses the issue of how to construct
   suitable aggregates of individual journal rankings, using an
   optimization-based consensus ranking approach. The authors apply the
   proposed method to a subset of marketing-related journals from a list of
   collected journal rankings. Next, the paper studies the stability of the
   derived consensus solution, and the degeneration effects that occur when
   excluding journals and/or rankings. Finally, the authors investigate the
   similarities/dissimilarities of the consensus with a naive meta-ranking
   and with individual rankings. The results show that, even though
   journals are not uniformly ranked, one may derive a consensus ranking
   with considerably high agreement with the individual rankings. (C) 2013
   Elsevier Inc. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE INC}},
Address = {{360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Theussl, S (Reprint Author), WU Vienna Univ Econ \& Business, Inst Stat \& Math, Welthandelspl 1, A-1020 Vienna, Austria.
   Theussl, Stefan; Reutterer, Thomas; Hornik, Kurt, WU Vienna Univ Econ \& Business, A-1020 Vienna, Austria.}},
DOI = {{10.1016/j.jbusres.2013.08.006}},
ISSN = {{0148-2963}},
EISSN = {{1873-7978}},
Keywords = {{Journal ranking; Consensus ranking; Meta-ranking; Marketing; Binary
   optimization}},
Keywords-Plus = {{MANAGEMENT; BUSINESS}},
Research-Areas = {{Business \& Economics}},
Web-of-Science-Categories  = {{Business}},
Author-Email = {{stefan.theussl@wu.ac.at
   thomas.reutterer@wu.ac.at
   kurt.hornik@wu.ac.at}},
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Number-of-Cited-References = {{32}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{15}},
Journal-ISO = {{J. Bus. Res.}},
Doc-Delivery-Number = {{AE2AO}},
Unique-ID = {{ISI:000333775900051}},
}

@article{ ISI:000336087800012,
Author = {Brylinski, Michal and Waldrop, Grover L.},
Title = {{Computational Redesign of Bacterial Biotin Carboxylase Inhibitors Using
   Structure-Based Virtual Screening of Combinatorial Libraries}},
Journal = {{MOLECULES}},
Year = {{2014}},
Volume = {{19}},
Number = {{4}},
Pages = {{4021-4045}},
Month = {{APR}},
Abstract = {{As the spread of antibiotic resistant bacteria steadily increases, there
   is an urgent need for new antibacterial agents. Because fatty acid
   synthesis is only used for membrane biogenesis in bacteria, the enzymes
   in this pathway are attractive targets for antibacterial agent
   development. Acetyl-CoA carboxylase catalyzes the committed and
   regulated step in fatty acid synthesis. In bacteria, the enzyme is
   composed of three distinct protein components: biotin carboxylase,
   biotin carboxyl carrier protein, and carboxyltransferase. Fragment-based
   screening revealed that amino-oxazole inhibits biotin carboxylase
   activity and also exhibits antibacterial activity against Gram-negative
   organisms. In this report, we redesigned previously identified lead
   inhibitors to expand the spectrum of bacteria sensitive to the
   amino-oxazole derivatives by including Gram-positive species. Using
   9,411 small organic building blocks, we constructed a diverse
   combinatorial library of 1.2 x 10(8) amino-oxazole derivatives. A subset
   of 9 x 10(6) of these compounds were subjected to structure-based
   virtual screening against seven biotin carboxylase isoforms using
   similarity-based docking by eSimDock. Potentially broad-spectrum
   antibiotic candidates were selected based on the consensus ranking by
   several scoring functions including non-linear statistical models
   implemented in eSimDock and traditional molecular mechanics force
   fields. The analysis of binding poses of the top-ranked compounds docked
   to biotin carboxylase isoforms suggests that: (1) binding of the
   amino-oxazole anchor is stabilized by a network of hydrogen bonds to
   residues 201, 202 and 204; (2) halogenated aromatic moieties attached to
   the amino-oxazole scaffold enhance interactions with a hydrophobic
   pocket formed by residues 157, 169, 171 and 203; and (3) larger
   substituents reach deeper into the binding pocket to form additional
   hydrogen bonds with the side chains of residues 209 and 233. These
   structural insights into drug-biotin carboxylase interactions will be
   tested experimentally in in vitro and in vivo systems to increase the
   potency of amino-oxazole inhibitors towards both Gram-negative as well
   as Gram-positive species.}},
Publisher = {{MDPI AG}},
Address = {{POSTFACH, CH-4005 BASEL, SWITZERLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Brylinski, M (Reprint Author), Louisiana State Univ, Div Biochem \& Mol Biol, Baton Rouge, LA 70803 USA.
   Brylinski, Michal; Waldrop, Grover L., Louisiana State Univ, Div Biochem \& Mol Biol, Baton Rouge, LA 70803 USA.
   Brylinski, Michal; Waldrop, Grover L., Louisiana State Univ, Ctr Computat \& Technol, Baton Rouge, LA 70803 USA.}},
DOI = {{10.3390/molecules19044021}},
ISSN = {{1420-3049}},
Keywords = {{biotin carboxylase; acetyl-CoA carboxylase; biotin carboxylase
   inhibitors; amino-oxazole; combinatorial chemistry; cheminformatics;
   ligand docking; virtual screening; eSimDock}},
Keywords-Plus = {{ACETYL-COA CARBOXYLASE; FATTY-ACID BIOSYNTHESIS; DRUG DISCOVERY; FOCUSED
   LIBRARIES; ESCHERICHIA-COLI; DOCKING; DATABASE; LIGAND; DESIGN;
   PREDICTION}},
Research-Areas = {{Chemistry}},
Web-of-Science-Categories  = {{Chemistry, Organic}},
Author-Email = {{michal@brylinski.org
   gwaldro@lsu.edu}},
Funding-Acknowledgement = {{Louisiana Board of Regents through the Board of Regents Support Fund
   {[}LEQSF(2012-15)-RD-A-05]}},
Funding-Text = {{This study was supported by the Louisiana Board of Regents through the
   Board of Regents Support Fund {[}contract LEQSF(2012-15)-RD-A-05].
   Portions of this research were conducted with high performance
   computational resources provided by Louisiana State University (HPC@LSU)
   and the Louisiana Optical Network Institute (LONI).}},
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Number-of-Cited-References = {{58}},
Times-Cited = {{3}},
Usage-Count-(Last-180-days) = {{9}},
Usage-Count-Since-2013 = {{20}},
Journal-ISO = {{Molecules}},
Doc-Delivery-Number = {{AH4HK}},
Unique-ID = {{ISI:000336087800012}},
}

@article{ ISI:000335390000010,
Author = {Faria, Fabio A. and Pedronette, Daniel C. G. and dos Santos, Jefersson
   A. and Rocha, Anderson and Torres, Ricardo da S.},
Title = {{Rank Aggregation for Pattern Classifier Selection in Remote Sensing
   Images}},
Journal = {{IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE
   SENSING}},
Year = {{2014}},
Volume = {{7}},
Number = {{4}},
Pages = {{1103-1115}},
Month = {{APR}},
Abstract = {{In the past few years, segmentation and classification techniques have
   become a cornerstone of many successful remote sensing algorithms aiming
   at delineating geographic target objects. One common strategy relies on
   using multiple complex features to guide the delineation process with
   the objective of gathering complementary information for improving
   classification results. However, a persistent problem in this approach
   is how to combine different and noncorrelated feature descriptors
   automatically. In this regard, one solution is to combine them through
   multiple classifier systems (MCSs) in which the diversity of
   simple/non-complex classifiers is an essential issue in the definition
   of appropriate strategies for classifier fusion. In this paper, we
   propose a novel strategy for selecting classifiers (whereby a classifier
   is taken as a pair of learning method plus image descriptor) to be
   combined in MCS. In the proposed solution, diversity measures are used
   to assess the degree of agreement/disagreement between pairs of
   classifiers and ranked lists are created to sort them according to their
   diversity score. Thereafter, the classifiers are also sorted according
   to their performance through different evaluation measures (e. g., kappa
   and tau indices). In the end, a rank aggregation method is proposed to
   select the most suitable classifiers based on both the diversity and the
   effectiveness performance of classifiers. The proposed fusion framework
   has targeted at coffee crop classification and urban recognition but it
   is general enough to be used in a variety of other pattern recognition
   problems. Experimental results demonstrate that the novel strategy
   yields good results when compared to several baselines while using fewer
   classifiers and being much more efficient.}},
Publisher = {{IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC}},
Address = {{445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Faria, FA (Reprint Author), Univ Estadual Campinas, Inst Comp, BR-13083852 Sao Paulo, Brazil.
   Faria, Fabio A.; Rocha, Anderson; Torres, Ricardo da S., Univ Estadual Campinas, Inst Comp, BR-13083852 Sao Paulo, Brazil.
   Pedronette, Daniel C. G., State Univ Sao Paulo UNESP, Dept Stat Appl Math \& Comp, BR-13506900 Sao Paulo, Brazil.
   dos Santos, Jefersson A., Univ Fed Minas Gerais, Dept Comp Sci, BR-31270010 Belo Horizonte, MG, Brazil.}},
DOI = {{10.1109/JSTARS.2014.2303813}},
ISSN = {{1939-1404}},
EISSN = {{2151-1535}},
Keywords = {{Coffee crop classification; diversity measures; information fusion;
   meta-learning; urban recognition}},
Keywords-Plus = {{FUSION; TEXTURE; RECOGNITION; ACCURACY; SCALE}},
Research-Areas = {{Engineering; Physical Geography; Remote Sensing; Imaging Science \&
   Photographic Technology}},
Web-of-Science-Categories  = {{Engineering, Electrical \& Electronic; Geography, Physical; Remote
   Sensing; Imaging Science \& Photographic Technology}},
Author-Email = {{ffaria@ic.unicamp.br
   daniel@rc.unesp.br
   jefersson@dcc.ufmg.br
   rocha.anderson@ic.unicamp.br
   rtorres@ic.unicamp.br}},
ResearcherID-Numbers = {{Pedronette, Daniel/E-7817-2015}},
Funding-Acknowledgement = {{CAPES {[}1260-12-0]; CNPq {[}306580/2012-8, 484254/2012-0,
   304352/2012-8]; Sao Paulo Research Foundation-FAPESP {[}2010/14910-0,
   2010/05647-4, 2012/18768-0, 2013/08645-0]; Microsoft Research}},
Funding-Text = {{The work was supported in part by CAPES (Grant 1260-12-0), in part by
   CNPq (Grants 306580/2012-8, 484254/2012-0, and 304352/2012-8), in part
   by Sao Paulo Research Foundation-FAPESP (Grants 2010/14910-0,
   2010/05647-4, 2012/18768-0, and 2013/08645-0), and in part by Microsoft
   Research.}},
Cited-References = {{dos Santos JA, 2013, IEEE J-STARS, V6, P2020, DOI 10.1109/JSTARS.2012.2237013.
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Number-of-Cited-References = {{49}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{19}},
Journal-ISO = {{IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens.}},
Doc-Delivery-Number = {{AG4LB}},
Unique-ID = {{ISI:000335390000010}},
}

@article{ ISI:000333209300007,
Author = {Guimaraes Pedronette, Daniel Carlos and Torres, Ricardo da Silva and
   Calumby, Rodrigo Tripodi},
Title = {{Using contextual spaces for image re-ranking and rank aggregation}},
Journal = {{MULTIMEDIA TOOLS AND APPLICATIONS}},
Year = {{2014}},
Volume = {{69}},
Number = {{3}},
Pages = {{689-716}},
Month = {{APR}},
Abstract = {{This article presents two novel re-ranking approaches that take into
   account contextual information defined by the K-Nearest Neighbours (KNN)
   of a query image for improving the effectiveness of CBIR systems. The
   main contributions of this article are the definition of the concept of
   contextual spaces for encoding contextual information of images; the
   definition of two new re-ranking algorithms that exploit contextual
   information encoded in contextual spaces; and the evaluation of the
   proposed algorithms in several CBIR tasks related to the combination of
   image descriptors; combination of visual and textual descriptors; and
   combination of post-processing (re-ranking) methods. We conducted a
   large evaluation protocol involving visual descriptors (considering
   shape, color, and texture) and textual descriptors, various datasets,
   and comparisons with other post-processing methods. Experimental results
   demonstrate the effectiveness of our approaches.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Pedronette, DCG (Reprint Author), Univ Estadual Campinas, Recod Lab, Inst Comp, Campinas, SP, Brazil.
   Guimaraes Pedronette, Daniel Carlos; Torres, Ricardo da Silva; Calumby, Rodrigo Tripodi, Univ Estadual Campinas, Recod Lab, Inst Comp, Campinas, SP, Brazil.
   Calumby, Rodrigo Tripodi, Univ Feira de Santana, Dept Exact Sci, Feira De Santana, Brazil.}},
DOI = {{10.1007/s11042-012-1115-z}},
ISSN = {{1380-7501}},
EISSN = {{1573-7721}},
Keywords = {{Content-based image retrieval; Re-ranking; Rank aggregation; Contextual
   information; Multimodal retrieval}},
Keywords-Plus = {{SHAPE RETRIEVAL; CLASSIFICATION; TRANSDUCTION; CORRELOGRAMS;
   RECOGNITION; INFORMATION; SIMILARITY; DESCRIPTOR; DISTANCE}},
Research-Areas = {{Computer Science; Engineering}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Computer Science, Software
   Engineering; Computer Science, Theory \& Methods; Engineering,
   Electrical \& Electronic}},
Author-Email = {{dcarlos@ic.unicamp.br
   rtorres@ic.unicamp.br
   tripodi@ic.unicamp.br}},
ResearcherID-Numbers = {{Pedronette, Daniel/E-7817-2015}},
Funding-Acknowledgement = {{AMD; FAEPEX {[}2007/-52015-0, 2009/-18438-7]; CAPES; FAPESP; CNPq;
   DGA/-UNICAMP}},
Funding-Text = {{Authors thank AMD, FAEPEX (grants 2007/-52015-0 and 2009/-18438-7),
   CAPES, FAPESP, and CNPq for financial support. Authors also thank
   DGA/-UNICAMP for its support in this work.}},
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Number-of-Cited-References = {{50}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{12}},
Journal-ISO = {{Multimed. Tools Appl.}},
Doc-Delivery-Number = {{AD4HM}},
Unique-ID = {{ISI:000333209300007}},
}

@article{ ISI:000331854700009,
Author = {Fabian, Junior and Pires, Ramon and Rocha, Anderson},
Title = {{Visual words dictionaries and fusion techniques for searching people
   through textual and visual attributes}},
Journal = {{PATTERN RECOGNITION LETTERS}},
Year = {{2014}},
Volume = {{39}},
Number = {{SI}},
Pages = {{74-84}},
Month = {{APR 1}},
Abstract = {{Using personal traits for searching people is paramount in several
   application areas and has attracted an ever-growing attention from the
   scientific community over the past years. Some practical applications in
   the realm of digital forensics and surveillance include locating a
   suspect or finding missing people in a public space. In this paper, we
   aim at assigning describable visual attributes (e.g., white chubby male
   wearing glasses and with bangs) as labels to images to describe their
   appearance and performing visual searches without relying on image
   annotations during testing. For that, we create mid-level image
   representations for face images based on visual dictionaries linking
   visual properties in the images to describable attributes. In addition,
   we take advantage of machine learning techniques for combining different
   attributes and performing a query. First, we propose three methods for
   building the visual dictionaries. Method \#1 uses a sparse-sampling
   scheme to obtain low-level features with a clustering algorithm to build
   the visual dictionaries. Method \#2 uses dense-sampling to obtain
   low-level features and random selection to build the visual dictionaries
   while Method \#3 uses dense-sampling to obtain low-level features
   followed by a clustering algorithm to build the visual dictionaries.
   Thereafter, we train 2-class classifiers for the describable visual
   attributes of interest which assign to each image a decision score used
   to obtain its ranking. For more complex queries (2+ attributes), we use
   three state-of-the-art approaches for combining the rankings: (1)
   product of probabilities, (2) rank aggregation and (3) rank position. To
   date, we have considered fifteen attribute classifiers and,
   consequently, their direct counterparts theoretically allowing 2(15) =
   32,768 different combined queries (the actual number is smaller since
   some attributes are contradictory or mutually exclusive).
   Notwithstanding, the method is easily extensible to include new
   attributes. Experimental results show that Method \#3 greatly improves
   retrieval precision for some attributes in comparison with other methods
   in the literature. Finally, for combined attributes, product of
   probabilities, rank aggregation and rank position yield complementary
   results for rank fusion and the final decision making suggesting
   interesting possible combinations for further work. (C) 2013 Elsevier
   B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Rocha, A (Reprint Author), Univ Campinas Unicamp, Inst Comp, Av Albert Einstein 1251, BR-13083852 Campinas, SP, Brazil.
   Fabian, Junior; Pires, Ramon; Rocha, Anderson, Univ Campinas Unicamp, Inst Comp, BR-13083852 Campinas, SP, Brazil.}},
DOI = {{10.1016/j.patrec.2013.09.011}},
ISSN = {{0167-8655}},
EISSN = {{1872-7344}},
Keywords = {{Face search; Attribute classifiers; Rank fusion; Visual dictionaries;
   Dense-sampling characterization}},
Keywords-Plus = {{IMAGE CLASSIFICATION; RETRIEVAL; FEATURES}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{jfabian@recod.ic.unicamp.br
   pires.ramon@students.ic.unicamp.br
   anderson.rocha@ic.unicamp.br}},
Funding-Acknowledgement = {{Microsoft Research; Sao Paulo Research Foundation (FAPESP)
   {[}2010/05647-4]; National Council for Scientific and Technological
   Development (CNPq) {[}304352/2012-8]}},
Funding-Text = {{We thank Microsoft Research, Sao Paulo Research Foundation (FAPESP),
   Grant 2010/05647-4, and National Council for Scientific and
   Technological Development (CNPq), Grant 304352/2012-8 for the financial
   support. We also thank Prof. Dr. Eduardo Valle for valuable suggestions
   on earlier drafts of this manuscript.}},
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Number-of-Cited-References = {{39}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{18}},
Journal-ISO = {{Pattern Recognit. Lett.}},
Doc-Delivery-Number = {{AB5UR}},
Unique-ID = {{ISI:000331854700009}},
}

@article{ ISI:000334044600003,
Author = {Sarkar, Chandrima and Cooley, Sarah and Srivastava, Jaideep},
Title = {{Robust Feature Selection Technique Using Rank Aggregation}},
Journal = {{APPLIED ARTIFICIAL INTELLIGENCE}},
Year = {{2014}},
Volume = {{28}},
Number = {{3, SI}},
Pages = {{243-257}},
Month = {{MAR 16}},
Abstract = {{Although feature selection is a well-developed research area, there is
   an ongoing need to develop methods to make classifiers more efficient.
   One important challenge is the lack of a universal feature selection
   technique that produces similar outcomes with all types of classifiers.
   This is because all feature selection techniques have individual
   statistical biases, whereas classifiers exploit different statistical
   properties of data for evaluation. In numerous situations, this can put
   researchers into dilemma with regard to which feature selection method
   and classifiers to choose from a vast range of choices. In this article,
   we propose a technique that aggregates the consensus properties of
   various feature selection methods in order to develop a more optimal
   solution. The ensemble nature of our technique makes it more robust
   across various classifiers. In other words, it is stable toward
   achieving similar and, ideally, higher classification accuracy across a
   wide variety of classifiers. We quantify this concept of robustness with
   a measure known as the robustness index (RI). We perform an extensive
   empirical evaluation of our technique on eight datasets with different
   dimensions, including arrythmia, lung cancer, Madelon, mfeat-fourier,
   Internet ads, leukemia-3c, embryonal tumor, and a real-world dataset,
   vis., acute myeloid leukemia (AML). We demonstrate not only that our
   algorithm is more robust, but also that, compared with other techniques,
   our algorithm improves the classification accuracy by approximately
   3-4\% in a dataset with fewer than 500 features and by more than 5\% in
   a dataset with more than 500 features, across a wide range of
   classifiers.}},
Publisher = {{TAYLOR \& FRANCIS INC}},
Address = {{520 CHESTNUT STREET, STE 850, PHILADELPHIA, PA 19106 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Sarkar, C (Reprint Author), Univ Minnesota Twin Cities, Coll Sci \& Engn, Dept Comp Sci, 4-192 Keller Hall,200 Union St, Minneapolis, MN 55455 USA.
   Sarkar, Chandrima; Srivastava, Jaideep, Univ Minnesota Twin Cities, Coll Sci \& Engn, Minneapolis, MN 55455 USA.
   Cooley, Sarah, Univ Minnesota Twin Cities, Mason Canc Ctr, St Paul, MN USA.}},
DOI = {{10.1080/08839514.2014.883903}},
ISSN = {{0883-9514}},
EISSN = {{1087-6545}},
Research-Areas = {{Computer Science; Engineering}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Engineering, Electrical \&
   Electronic}},
Author-Email = {{sark0071@umn.edu}},
Funding-Acknowledgement = {{National Institutes of Health/NCI {[}P01 111412]}},
Funding-Text = {{AML data resource in this work was supported by the National Institutes
   of Health/NCI grant P01 111412, PI Jeffrey S. Miller, M. D, utilizing
   the Masonic Cancer Center, University of Minnesota Oncology Medical
   Informatics shared resources. We would like to thank Atanu Roy for his
   critical reviews and technical feedback during the development of this
   research.}},
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Number-of-Cited-References = {{23}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{15}},
Journal-ISO = {{Appl. Artif. Intell.}},
Doc-Delivery-Number = {{AE5QU}},
Unique-ID = {{ISI:000334044600003}},
}

@article{ ISI:000332354200028,
Author = {van Zuylen, Anke and Schalekamp, Frans and Williamson, David P.},
Title = {{Popular ranking}},
Journal = {{DISCRETE APPLIED MATHEMATICS}},
Year = {{2014}},
Volume = {{165}},
Number = {{SI}},
Pages = {{312-316}},
Month = {{MAR 11}},
Abstract = {{In this paper we take a new approach to the very old problem of
   aggregating preferences of multiple agents. We define the notion of
   popular ranking: a ranking of a set of elements is popular if there
   exists no other permutation of the elements that a majority of the
   voters prefer. We show that such a permutation is unlikely to exist: we
   show that a necessary but not sufficient condition for the existence of
   a popular ranking is Condorcet's paradox not occurring. In addition, we
   show that if Condorcet's paradox does not occur, then we can efficiently
   compute a permutation, which may or may not be popular, but for which
   the voters will have to solve an NP-hard problem to compute a
   permutation that a majority of them prefer. (C) 2014 Published by
   Elsevier B.V.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{van Zuylen, A (Reprint Author), Max Planck Inst Informat, D-66123 Saarbrucken, Germany.
   van Zuylen, Anke, Max Planck Inst Informat, D-66123 Saarbrucken, Germany.
   Schalekamp, Frans, Coll William \& Mary, Dept Math, Williamsburg, VA 23187 USA.
   Williamson, David P., Cornell Univ, Sch ORIE, Ithaca, NY USA.}},
DOI = {{10.1016/j.dam.2012.07.006}},
ISSN = {{0166-218X}},
EISSN = {{1872-6771}},
Keywords = {{Rank aggregation; Kemeny rank aggregation; Popular ranking}},
Keywords-Plus = {{ELECTION}},
Research-Areas = {{Mathematics}},
Web-of-Science-Categories  = {{Mathematics, Applied}},
Author-Email = {{anke@mpi-inf.mpg.de
   fms9@cornell.edu
   dpw@cs.cornell.edu}},
Funding-Acknowledgement = {{Berlin Mathematical School; Alexander von Humboldt Foundation}},
Funding-Text = {{This work was performed while the third author was on sabbatical at TU
   Berlin and he was supported by the Berlin Mathematical School and the
   Alexander von Humboldt Foundation.}},
Cited-References = {{Faliszewski P, 2010, COMMUN ACM, V53, P74, DOI 10.1145/1839676.1839696.
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Number-of-Cited-References = {{10}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Discret Appl. Math.}},
Doc-Delivery-Number = {{AC2SL}},
Unique-ID = {{ISI:000332354200028}},
}

@article{ ISI:000335458100010,
Author = {Volkovs, Maksims N. and Zemel, Richard S.},
Title = {{New Learning Methods for Supervised and Unsupervised Preference
   Aggregation}},
Journal = {{JOURNAL OF MACHINE LEARNING RESEARCH}},
Year = {{2014}},
Volume = {{15}},
Pages = {{1135-1176}},
Month = {{MAR}},
Abstract = {{In this paper we present a general treatment of the preference
   aggregation problem, in which multiple preferences over objects must be
   combined into a single consensus ranking. We consider two instances of
   this problem: unsupervised aggregation where no information about a
   target ranking is available, and supervised aggregation where ground
   truth preferences are provided. For each problem class we develop novel
   learning methods that are applicable to a wide range of preference
   types.(1) Specifically, for unsupervised aggregation we introduce the
   Multinomial Preference model (MPM) which uses a multinomial generative
   process to model the observed preferences. For the supervised problem we
   develop a supervised extension for MPM and then propose two fully
   supervised models. The first model employs SVD factorization to derive
   effective item features, transforming the aggregation problems into a
   learning-to-rank one. The second model aims to eliminate the costly SVD
   factorization and instantiates a probabilistic CRF framework, deriving
   unary and pairwise potentials directly from the observed preferences.
   Using a probabilistic framework allows us to directly optimize the
   expectation of any target metric, such as NDCG or ERR. All the proposed
   models operate on pairwise preferences and can thus be applied to a wide
   range of preference types. We empirically validate the models on rank
   aggregation and collaborative filtering data sets and demonstrate
   superior empirical accuracy.}},
Publisher = {{MICROTOME PUBL}},
Address = {{31 GIBBS ST, BROOKLINE, MA 02446 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Volkovs, MN (Reprint Author), Univ Toronto, 40 St George St, Toronto, ON M5S 2E4, Canada.
   Volkovs, Maksims N.; Zemel, Richard S., Univ Toronto, Toronto, ON M5S 2E4, Canada.}},
ISSN = {{1532-4435}},
Keywords = {{preference aggregation; meta-search; learning-to-rank; collaborative
   filtering}},
Research-Areas = {{Automation \& Control Systems; Computer Science}},
Web-of-Science-Categories  = {{Automation \& Control Systems; Computer Science, Artificial Intelligence}},
Author-Email = {{MVOLKOVS@CS.TORONTO.EDU
   ZEMEL@CS.TORONTO.EDU}},
Funding-Acknowledgement = {{Canadian Natural Sciences and Engineering Council (NSERC); Canadian
   Institute for Advanced Research (CIFAR)}},
Funding-Text = {{We would like to thank Craig Boutilier, Hugo Larochelle, and Ruslan
   Salakhutdinov for many thoughtful discussions and suggestions. This
   research was supported by the Canadian Natural Sciences and Engineering
   Council (NSERC) and the Canadian Institute for Advanced Research
   (CIFAR).}},
Cited-References = {{Agichtein E., 2006, INT ACM SIGIR C RES.
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   Volkovs M. N., 2013, INT C INF KNOWL MAN.}},
Number-of-Cited-References = {{54}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{J. Mach. Learn. Res.}},
Doc-Delivery-Number = {{AG5KO}},
Unique-ID = {{ISI:000335458100010}},
}

@article{ ISI:000332259300021,
Author = {Sun, Haoqi and Wang, Haiping and Zhu, Ruixin and Tang, Kailin and Gong,
   Qin and Cui, Juan and Cao, Zhiwei and Liu, Qi},
Title = {{iPEAP: integrating multiple omics and genetic data for pathway
   enrichment analysis}},
Journal = {{BIOINFORMATICS}},
Year = {{2014}},
Volume = {{30}},
Number = {{5}},
Pages = {{737-739}},
Month = {{MAR 1}},
Abstract = {{A challenge in biodata analysis is to understand the underlying
   phenomena among many interactions in signaling pathways. Such study is
   formulated as the pathway enrichment analysis, which identifies relevant
   pathways functional enriched in highthroughput data. The question faced
   here is how to analyze different data types in a unified and integrative
   way by characterizing pathways that these data simultaneously reveal. To
   this end, we developed integrative Pathway Enrichment Analysis Platform,
   iPEAP, which handles transcriptomics, proteomics, metabolomics and GWAS
   data under a unified aggregation schema. iPEAP emphasizes on the ability
   to aggregate various pathway enrichment results generated in different
   high-throughput experiments, as well as the quantitative measurements of
   different ranking results, thus providing the first benchmark platform
   for integration, comparison and evaluation of multiple types of data and
   enrichment methods.}},
Publisher = {{OXFORD UNIV PRESS}},
Address = {{GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Sun, HQ (Reprint Author), Tongji Univ, Sch Life Sci \& Technol, Dept Bioinformat, Siping Rd 1239, Shanghai 200092, Peoples R China.
   Sun, Haoqi; Zhu, Ruixin; Tang, Kailin; Gong, Qin; Cao, Zhiwei; Liu, Qi, Tongji Univ, Sch Life Sci \& Technol, Dept Bioinformat, Shanghai 200092, Peoples R China.
   Wang, Haiping, Hefei Univ Technol, Dept Comp Sci, Hefei 230009, Peoples R China.
   Cui, Juan, Univ Georgia, Dept Biochem \& Mol Biol, Athens, GA 30602 USA.}},
DOI = {{10.1093/bioinformatics/btt576}},
ISSN = {{1367-4803}},
EISSN = {{1460-2059}},
Keywords-Plus = {{RANK AGGREGATION; LEVEL ANALYSIS; EXPRESSION; TRANSCRIPTOMICS;
   METAANALYSIS}},
Research-Areas = {{Biochemistry \& Molecular Biology; Biotechnology \& Applied
   Microbiology; Computer Science; Mathematical \& Computational Biology;
   Mathematics}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Biotechnology \& Applied Microbiology;
   Computer Science, Interdisciplinary Applications; Mathematical \&
   Computational Biology; Statistics \& Probability}},
Funding-Acknowledgement = {{National Natural Science Foundation of China {[}31100956, 61173117];
   National 863 program {[}2012AA020405, 2012AA011005]}},
Funding-Text = {{National Natural Science Foundation of China (31100956 and 61173117) and
   National 863 program (2012AA020405 and 2012AA011005).}},
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Number-of-Cited-References = {{18}},
Times-Cited = {{6}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{18}},
Journal-ISO = {{Bioinformatics}},
Doc-Delivery-Number = {{AC1ML}},
Unique-ID = {{ISI:000332259300021}},
}

@article{ ISI:000332905300003,
Author = {Guimaraes Pedronette, Daniel Carlos and Penatti, Otavio A. B. and
   Torres, Ricardo da S.},
Title = {{Unsupervised manifold learning using Reciprocal kNN Graphs in image
   re-ranking and rank aggregation tasks}},
Journal = {{IMAGE AND VISION COMPUTING}},
Year = {{2014}},
Volume = {{32}},
Number = {{2}},
Pages = {{120-130}},
Month = {{FEB}},
Abstract = {{In this paper, we present an unsupervised distance learning approach for
   improving the effectiveness of image retrieval tasks. We propose a
   Reciprocal kNN Graph algorithm that considers the relationships among
   ranked lists in the context of a k-reciprocal neighborhood. The
   similarity is propagated among neighbors considering the geometry of the
   dataset manifold. The proposed method can be used both for re-ranking
   and rank aggregation tasks. Unlike traditional diffusion process
   methods, which require matrix multiplication operations, our algorithm
   takes only a subset of ranked lists as input, presenting linear
   complexity in terms of computational and storage requirements. We
   conducted a large evaluation protocol involving shape, color, and
   texture descriptors, various datasets, and comparisons with other
   post-processing approaches. The re-ranking and rank aggregation
   algorithms yield better results in terms of effectiveness performance
   than various state-of-the-art algorithms recently proposed in the
   literature, achieving bull's eye and MAP scores of 100\% on the
   well-known MPEG-7 shape dataset (C) 2013 Elsevier B.V. All rights
   reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Pedronette, DCG (Reprint Author), Univ Estadual Paulista UNESP, Dept Stat Appl Math \& Comp, Av 24-A,1515, BR-13506900 Rio Claro, SP, Brazil.
   Guimaraes Pedronette, Daniel Carlos, Univ Estadual Paulista UNESP, Dept Stat Appl Math \& Comp, BR-13506900 Rio Claro, SP, Brazil.
   Penatti, Otavio A. B.; Torres, Ricardo da S., Univ Estadual Campinas, IC, RECOD Lab, BR-13083852 Campinas, SP, Brazil.
   Penatti, Otavio A. B., SAMSUNG Res Inst, BR-13097104 Campinas, SP, Brazil.}},
DOI = {{10.1016/j.imavis.2013.12.009}},
ISSN = {{0262-8856}},
EISSN = {{1872-8138}},
Keywords = {{Content-based image retrieval; Re-ranking; Rank aggregation}},
Keywords-Plus = {{SHAPE; RECOGNITION; RETRIEVAL; CLASSIFICATION; DISTANCE}},
Research-Areas = {{Computer Science; Engineering; Optics}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Computer Science, Software
   Engineering; Computer Science, Theory \& Methods; Engineering,
   Electrical \& Electronic; Optics}},
Author-Email = {{daniel@rc.unesp.br
   penatti@ic.unicamp.br
   rtorres@ic.unicamp.br}},
ResearcherID-Numbers = {{Pedronette, Daniel/E-7817-2015}},
Funding-Acknowledgement = {{AMD; FAEPEX; CAPES; FAPESP; CNPq}},
Funding-Text = {{Authors thank AMD, FAEPEX, CAPES, FAPESP, and CNPq for financial
   support.}},
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Number-of-Cited-References = {{46}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{9}},
Journal-ISO = {{Image Vis. Comput.}},
Doc-Delivery-Number = {{AD0DS}},
Unique-ID = {{ISI:000332905300003}},
}

@article{ ISI:000331781300011,
Author = {Zhang, Liyuan and Li, Tao and Xu, Xuanhua},
Title = {{Consensus model for multiple criteria group decision making under
   intuitionistic fuzzy environment}},
Journal = {{KNOWLEDGE-BASED SYSTEMS}},
Year = {{2014}},
Volume = {{57}},
Pages = {{127-135}},
Month = {{FEB}},
Abstract = {{Group decision making with consensus requirement is the process of
   reaching group consensus, ranking the feasible alternatives and
   selecting the best one. In this paper, we develop a methodology for
   fuzzy group decision making with group consensus. Firstly, each expert
   makes his/her judgement on each alternative with respect to multiple
   criteria by the intuitionistic fuzzy sets, the group preference vectors
   for each alternative are calculated by the formula. Secondly, the
   similarity measure between two intuitionistic fuzzy sets is defined to
   compute each expert's decision deviation, a threshold value is used to
   determine the decision deviation whether be acceptable. Then, based on
   the expert's group consensus decision information, the group matrix is
   obtained by weighted similarity measure. Using the ordered weight
   operator, the order of the alternatives is got and the best one can be
   easily selected. Finally, we apply our method to facility location
   selection problem and the other group consensus example in {[}3] to
   verify our methodology's feasibility and effectiveness. (C) 2013
   Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Li, T (Reprint Author), Shandong Univ Technol, Sch Sci, Zibo 255049, Peoples R China.
   Zhang, Liyuan, Shandong Univ Technol, Sch Business, Zibo 255049, Peoples R China.
   Li, Tao, Shandong Univ Technol, Sch Sci, Zibo 255049, Peoples R China.
   Xu, Xuanhua, Cent S Univ, Sch Business, Changsha 410083, Hunan, Peoples R China.}},
DOI = {{10.1016/j.knosys.2013.12.013}},
ISSN = {{0950-7051}},
EISSN = {{1872-7409}},
Keywords = {{Fuzzy group decision making; Group consensus; Similarity measure;
   Intuitionistic fuzzy set; Threshold value}},
Keywords-Plus = {{SIMILARITY MEASURES; SETS; AGGREGATION}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{liltaot@126.com}},
Funding-Acknowledgement = {{National Natural Science Foundation of China {[}11301306, 70871121,
   71371112]; Science Foundation for National Innovation Research Group of
   China {[}70921001]}},
Funding-Text = {{The research is supported by the National Natural Science Foundation of
   China (No. 11301306, 70871121, 71371112) and the Science Foundation for
   National Innovation Research Group of China (No. 70921001).}},
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Number-of-Cited-References = {{29}},
Times-Cited = {{7}},
Usage-Count-(Last-180-days) = {{5}},
Usage-Count-Since-2013 = {{30}},
Journal-ISO = {{Knowledge-Based Syst.}},
Doc-Delivery-Number = {{AB4SX}},
Unique-ID = {{ISI:000331781300011}},
}

@article{ ISI:000330231100011,
Author = {Widau, Ryan C. and Parekh, Akash D. and Ranck, Mark C. and Golden,
   Daniel W. and Kumar, Kiran A. and Sood, Ravi F. and Pitroda, Sean P. and
   Liao, Zhengkai and Huang, Xiaona and Darga, Thomas E. and Xu, David and
   Huang, Lei and Andrade, Jorge and Roizman, Bernard and Weichselbaum,
   Ralph R. and Khodarev, Nikolai N.},
Title = {{RIG-I-like receptor LGP2 protects tumor cells from ionizing radiation}},
Journal = {{PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF
   AMERICA}},
Year = {{2014}},
Volume = {{111}},
Number = {{4}},
Pages = {{E484-E491}},
Month = {{JAN 28}},
Abstract = {{An siRNA screen targeting 89 IFN stimulated genes in 14 different cancer
   cell lines pointed to the RIG-I (retinoic acid inducible gene I)like
   receptor Laboratory of Genetics and Physiology 2 (LGP2) as playing a key
   role in conferring tumor cell survival following cytotoxic stress
   induced by ionizing radiation (IR). Studies on the role of LGP2 revealed
   the following: (i) Depletion of LGP2 in three cancer cell lines resulted
   in a significant increase in cell death following IR, (ii) ectopic
   expression of LGP2 in cells increased resistance to IR, and (iii) IR
   enhanced LGP2 expression in three cell lines tested. Studies designed to
   define the mechanism by which LGP2 acts point to its role in regulation
   of IFN beta. Specifically (i) suppression of LGP2 leads to enhanced IFN
   beta, (ii) cytotoxic effects following IR correlated with expression of
   IFN beta inasmuch as inhibition of IFN beta by neutralizing antibody
   conferred resistance to cell death, and (iii) mouse embryonic
   fibroblasts from IFN receptor 1 knockout mice are radioresistant
   compared with wild-type mouse embryonic fibroblasts. The role of LGP2 in
   cancer may be inferred from cumulative data showing elevated levels of
   LGP2 in cancer cells are associated with more adverse clinical outcomes.
   Our results indicate that cytotoxic stress exemplified by IR induces IFN
   beta and enhances the expression of LGP2. Enhanced expression of LGP2
   suppresses the IFN stimulated genes associated with cytotoxic stress by
   turning off the expression of IFN beta.}},
Publisher = {{NATL ACAD SCIENCES}},
Address = {{2101 CONSTITUTION AVE NW, WASHINGTON, DC 20418 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Roizman, B (Reprint Author), Univ Chicago, Marjorie B Kovler Viral Oncol Labs, 910 E 58th St, Chicago, IL 60637 USA.
   Widau, Ryan C.; Parekh, Akash D.; Ranck, Mark C.; Golden, Daniel W.; Kumar, Kiran A.; Sood, Ravi F.; Pitroda, Sean P.; Liao, Zhengkai; Huang, Xiaona; Darga, Thomas E.; Xu, David; Weichselbaum, Ralph R.; Khodarev, Nikolai N., Univ Chicago, Dept Radiat \& Cellular Oncol, Chicago, IL 60637 USA.
   Widau, Ryan C.; Parekh, Akash D.; Ranck, Mark C.; Golden, Daniel W.; Kumar, Kiran A.; Sood, Ravi F.; Pitroda, Sean P.; Liao, Zhengkai; Huang, Xiaona; Darga, Thomas E.; Xu, David; Weichselbaum, Ralph R.; Khodarev, Nikolai N., Univ Chicago, Ludwig Ctr Metastasis Res, Chicago, IL 60637 USA.
   Huang, Lei; Andrade, Jorge, Univ Chicago, Ctr Res Informat, Chicago, IL 60637 USA.
   Roizman, Bernard, Univ Chicago, Marjorie B Kovler Viral Oncol Labs, Chicago, IL 60637 USA.}},
DOI = {{10.1073/pnas.1323253111}},
ISSN = {{0027-8424}},
Keywords = {{innate immunity; cytoplasmic sensor; interferon beta; DHX58}},
Keywords-Plus = {{RNA HELICASE LGP2; RANK AGGREGATION; INNATE IMMUNITY; DNA-DAMAGE;
   BREAST; RESISTANCE; EXPRESSION; THERAPY; STAT1; RADIOTHERAPY}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{bernard.roizman@bsd.uchicago.edu}},
ORCID-Numbers = {{Darga, Thomas/0000-0002-8968-6701}},
Funding-Acknowledgement = {{Ludwig Center for Metastasis Research Grant; Center for Radiation
   Therapy; Chicago Tumor Institute; Ludwig Foundation for Cancer Research;
   Mr. and Mrs. Vincent Foglia and the Foglia Foundation; Lung Cancer
   Research Foundation; Cancer Research Foundation; National Institutes of
   Health {[}R0-1 CA111423, PO1-CA71933]}},
Funding-Text = {{We gratefully acknowledge Dr. Samuel Hellman and Dr. Byron Burnette
   (University of Chicago) for helpful discussion of the manuscript; Dr.
   Samuel Bettis, Dr. Siquan Chen, and Rita Grantner (Cell Screening
   Center, University of Chicago) for assistance with siRNA screen; Dr.
   Yang- Xin Fu (University of Chicago) for generously providing B6/ IFNAR1
   KO (IFN receptor type 1 knockout) mice; and Drs. Curt M. Horvath
   (Northwestern) and Michael Gale, Jr. (University of Washington) for
   generously providing LGP2 constructs. This work was supported in part by
   the Ludwig Center for Metastasis Research Grant, the Center for
   Radiation Therapy, the Chicago Tumor Institute, the Ludwig Foundation
   for Cancer Research, Mr. and Mrs. Vincent Foglia and the Foglia
   Foundation, Lung Cancer Research Foundation, the Cancer Research
   Foundation, and National Institutes of Health Grants R0-1 CA111423 and
   PO1-CA71933 ( to R.R.W.).}},
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Number-of-Cited-References = {{47}},
Times-Cited = {{8}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{15}},
Journal-ISO = {{Proc. Natl. Acad. Sci. U. S. A.}},
Doc-Delivery-Number = {{297BV}},
Unique-ID = {{ISI:000330231100011}},
}

@article{ ISI:000330062700001,
Author = {Hammami, Muhammad M. and Al-Gaai, Eman A. and Al-Jawarneh, Yussuf and
   Amer, Hala and Hammami, Muhammad B. and Eissa, Abdullah and Al Qadire,
   Mohammad},
Title = {{Patients' perceived purpose of clinical informed consent: Mill's
   individual autonomy model is preferred}},
Journal = {{BMC MEDICAL ETHICS}},
Year = {{2014}},
Volume = {{15}},
Month = {{JAN 10}},
Abstract = {{Background: Although informed consent is an integral part of clinical
   practice, its current doctrine remains mostly a matter of law and
   mainstream ethics rather than empirical research. There are scarce
   empirical data on patients' perceived purpose of informed consent, which
   may include administrative routine/courtesy gesture, simple honest
   permission, informed permission, patient-clinician shared
   decision-making, and enabling patient's self decision-making. Different
   purposes require different processes.
   Methods: We surveyed 488 adults who were planning to undergo or had
   recently undergone written informed consent-requiring procedures.
   Perceptions of informed consent purpose (from norm and current practice
   perspectives) were explored by asking respondents to rank (1 = most
   reflective) 10 randomly-presented statements: ``meaningless routine{''},
   ``courtesy gesture{''} ``litigation protection{''}, ``take away
   compensation rights{''}, ``inform patient', ``make sure patient
   understand{''}, ``document patient's decision{''}, ``discover patient's
   preferences{''}, ``have shared decision{''}, and ``help patient
   decide{''}.
   Results: Respondents' mean (SD) age was 38.3 (12.5); 50.4\% were males,
   56.8\% had >= college education, and 37.3\% had undergone a procedure.
   From the norm perspective, the least reflective statement was
   ``meaningless routine{''} (ranked 1-3 by 2.6\% of respondents) and the
   most reflective statements were ``help patient decide{''}, ``make sure
   patient understand{''}, and ``inform patient{''} (ranked 1-3 by 65\%,
   60\%, and 48\% of respondents with median {[}25\%, 75\%] ranking scores
   of 2 {[}1,5], 3 {[}2,4], and 4 {[}2,5], respectively). Compared to their
   counterparts, males and pre-procedure respondents ranked ``help patient
   decide{''} better, whereas females and post-procedure respondents ranked
   ``inform patient{''} better (p = 0.007 to p < 0.001). Age was associated
   with better ranking of ``help patient decide{''} and ``make sure patient
   understand{''} statements (p < 0.001 and p = 0.002, respectively), which
   were ranked 1-3 by only 46\% and 42\% of respondents from the current
   practice perspective (median ranking score 4 {[}2,6], p < 0.001 vs. norm
   perspective for both).
   Conclusions: 1) the informed consent process is important to patients,
   however, patients vary in their views of its purpose with the dominant
   view being enabling patients' self decision-making, 2) males,
   pre-procedure, and older patients more favor a self decision-making
   purpose, whereas females and post-procedure patients more favor an
   information disclosure purpose, and 3) more self decision-making and
   more effective information disclosure than is currently practiced are
   desired. An informed consent process consistent with Mill's individual
   autonomy model may be suitable for most patients.}},
Publisher = {{BIOMED CENTRAL LTD}},
Address = {{236 GRAYS INN RD, FLOOR 6, LONDON WC1X 8HL, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Hammami, MM (Reprint Author), King Faisal Specialist Hosp \& Res Ctr, Clin Studies \& Empir Ethics Dept, POB 3354 MBC 03, Riyadh 11211, Saudi Arabia.
   Hammami, Muhammad M.; Al-Gaai, Eman A.; Al-Jawarneh, Yussuf; Amer, Hala; Hammami, Muhammad B.; Eissa, Abdullah; Al Qadire, Mohammad, King Faisal Specialist Hosp \& Res Ctr, Clin Studies \& Empir Ethics Dept, Riyadh 11211, Saudi Arabia.
   Hammami, Muhammad M., Alfaisal Univ, Coll Med, Riyadh, Saudi Arabia.}},
DOI = {{10.1186/1472-6939-15-2}},
Article-Number = {{2}},
ISSN = {{1472-6939}},
Keywords = {{Informed consent; Middle East; Norm perception; Current practice; Gender
   difference; Autonomy}},
Keywords-Plus = {{SHARED DECISION-MAKING; TREAT THEMSELVES; PATIENTS WANT; PERSPECTIVE;
   ILLNESS; INFORMATION; PHYSICIANS; SURGERY; HISTORY; WOMEN}},
Research-Areas = {{Social Sciences - Other Topics; Medical Ethics; Biomedical Social
   Sciences}},
Web-of-Science-Categories  = {{Ethics; Medical Ethics; Social Sciences, Biomedical}},
Author-Email = {{muhammad@kfshrc.edu.sa}},
Funding-Acknowledgement = {{King Faisal Specialist Hospital \& Research Center (KFSHRC)}},
Funding-Text = {{The study was funded by a grant from The King Faisal Specialist Hospital
   \& Research Center (KFSH\&RC) to MMH. KFSH\&RC had no role in study
   design; in the collection, analysis, and interpretation of data; in the
   writing of the manuscript; or in the decision to submit the manuscript
   for publication.}},
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Number-of-Cited-References = {{48}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{5}},
Usage-Count-Since-2013 = {{21}},
Journal-ISO = {{BMC Med. Ethics}},
Doc-Delivery-Number = {{294QU}},
Unique-ID = {{ISI:000330062700001}},
}

@article{ ISI:000328735700102,
Author = {Najafpanah, Mohammad Javad and Sadeghi, Mostafa and Bakhtiarizadeh,
   Mohammad Reza},
Title = {{Reference Genes Selection for Quantitative Real-Time PCR Using
   RankAggreg Method in Different Tissues of Capra hircus}},
Journal = {{PLOS ONE}},
Year = {{2013}},
Volume = {{8}},
Number = {{12}},
Month = {{DEC 16}},
Abstract = {{Identification of reference genes with stable levels of gene expression
   is an important prerequisite for obtaining reliable results in analysis
   of gene expression data using quantitative real time PCR (RT-qPCR).
   Since the underlying assumption of reference genes is that expressed at
   the exact same level in all sample types, in this study, we evaluated
   the expression stability of nine most commonly used endogenous controls
   (GAPDH, ACTB, 18S rRNA, RPS18, HSP-90, ALAS, HMBS, ACAC, and B2M) in
   four different tissues of the domestic goat, Capra hircus, including
   liver, visceral, subcutaneous fat and longissimus muscles, across
   different experimental treatments (a standard diet prepared using the
   NRC computer software as control and the same diet plus one mg
   chromium/day). We used six different software programs for ranking of
   reference genes and found that individual rankings of the genes differed
   among them. Additionally, there was a significant difference in ranking
   patterns of the studied genes among different tissues. A rank
   aggregation method was applied to combine the ranking lists of the six
   programs to a consensus ranking. Our results revealed that HSP-90 was
   nearly always among the two most stable genes in all studied tissues.
   Therefore, it is recommended for accurate normalization of RT-qPCR data
   in goats, while GAPDH, ACTB, and RPS18 showed the most varied
   expressions and should be avoided as reference genes.}},
Publisher = {{PUBLIC LIBRARY SCIENCE}},
Address = {{1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Najafpanah, MJ (Reprint Author), Univ Tehran, Dept Anim Sci, Coll Agr \& Nat Resources, Karaj, Iran.
   Najafpanah, Mohammad Javad; Sadeghi, Mostafa, Univ Tehran, Dept Anim Sci, Coll Agr \& Nat Resources, Karaj, Iran.
   Bakhtiarizadeh, Mohammad Reza, Univ Tehran, Dept Anim \& Poultry Sci, Coll Aburaihan, Tehran, Iran.}},
DOI = {{10.1371/journal.pone.0083041}},
Article-Number = {{e83041}},
ISSN = {{1932-6203}},
Keywords-Plus = {{POLYMERASE-CHAIN-REACTION; HUMAN ADIPOSE-TISSUE; RT-PCR; MESSENGER-RNA;
   CHROMIUM SUPPLEMENTATION; RELATIVE QUANTIFICATION; HOUSEKEEPING GENES;
   EXPRESSION; NORMALIZATION; VALIDATION}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{mjnajafpanah@alumni.ut.ac.ir
   sadeghimos@ut.ac.ir}},
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Number-of-Cited-References = {{54}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{12}},
Journal-ISO = {{PLoS One}},
Doc-Delivery-Number = {{276GD}},
Unique-ID = {{ISI:000328735700102}},
}

@article{ ISI:000323360500013,
Author = {Huang, Tony Cheng-Kui},
Title = {{A novel group ranking model for revealing sequence and quantity
   knowledge}},
Journal = {{EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}},
Year = {{2013}},
Volume = {{231}},
Number = {{3}},
Pages = {{654-666}},
Month = {{DEC 16}},
Abstract = {{The aggregation of individuals' preferences into a consensus ranking is
   a group ranking problem which has been widely utilized in various
   applications, such as decision support systems, recommendation systems,
   and voting systems. Gathering the comparison of preferences and
   aggregate them to gain consensuses is a conventional issue. For example,
   b > c >= d >= a indicates that b is favorable to c, and c (d) is
   somewhat favorable but not fully favorable to d (a), where > and >= are
   comparators, and a, b, c, and d are items. Recently, a new type of
   ranking model was proposed to provide temporal orders of items. The
   order, b\&c -> a, means that b and c can occur simultaneously and are
   also before a. Although this model can derive the order ranking of
   items, the knowledge about quantity-related items is also of importance
   to approach more real-life circumstances. For example, when enterprises
   or individuals handle their portfolios in financial management, two
   considerations, the sequences and the amount of money for investment
   objects, should be raised initially. In this study, we propose a model
   for discovering consensus sequential patterns with quantitative
   linguistic terms. Experiments using synthetic and real datasets showed
   the model's computational efficiency, scalability, and effectiveness.
   (c) 2013 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Huang, TCK (Reprint Author), Natl Chung Cheng Univ, Dept Business Adm, 168 Univ Rd, Chiayi, Taiwan.
   Natl Chung Cheng Univ, Dept Business Adm, Chiayi, Taiwan.}},
DOI = {{10.1016/j.ejor.2013.06.054}},
ISSN = {{0377-2217}},
Keywords = {{Group ranking; Data mining; Sequential data; Quantitative data;
   Linguistic terms}},
Keywords-Plus = {{GROUP DECISION-MAKING; PREFERENCE; INFORMATION; PROPOSALS; REVIEWERS;
   PATTERNS}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
Author-Email = {{bmahck@ccu.edu.tw}},
Funding-Acknowledgement = {{National Science Council of the Republic of China {[}NSC
   102-2410-H-194-100-MY2]}},
Funding-Text = {{The author would like to thank the Editor, Dr. Immanuel Bomze, and three
   anonymous referees for their helps and valuable comments to improve this
   paper. He also appreciates Krannert School of Management, Purdue
   University, providing the research resources to support the revision of
   this paper during his visiting period. This research was supported by
   the National Science Council of the Republic of China under the grant
   NSC 102-2410-H-194-100-MY2.}},
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Number-of-Cited-References = {{32}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{105}},
Journal-ISO = {{Eur. J. Oper. Res.}},
Doc-Delivery-Number = {{204JB}},
Unique-ID = {{ISI:000323360500013}},
}

@article{ ISI:000327685800029,
Author = {Huang, Tony Cheng-Kui},
Title = {{Recommendations of closed consensus temporal patterns by group decision
   making}},
Journal = {{KNOWLEDGE-BASED SYSTEMS}},
Year = {{2013}},
Volume = {{54}},
Number = {{SI}},
Pages = {{318-328}},
Month = {{DEC}},
Abstract = {{The aggregation of individuals' preferences into a consensus ranking is
   a decision support problem which has been widely used in various
   applications, such as decision support systems, voting systems, and
   recommendation systems. Especially when applying recommendation systems
   in business, customers ask for more suggestions about purchasing
   products or services because the tremendous amount of information
   available can be overwhelming. Therefore, we have to gather more
   preferences from recommenders and aggregate them to gain consensuses.
   For an example of preference ranking, C > A >= D >= B indicates C is
   favorable to A, A is somewhat favorable but not fully favorable to D,
   and ultimately D is somewhat favorable but not fully favorable to B,
   where > and are comparators, and A, B, C, and D are items. This shows
   the ranking relationship between items. However, no studies, to the best
   of our knowledge, have ever developed a recommendation system to suggest
   a temporal relationship between items. That is, ``item A could occur
   during the duration of item B{''} or ``item C could occur before item
   D{''}. This type of recommendation can be applied to the reading order
   of books, course plans in colleges, or the order of taking medicine for
   patients. This study proposes a novel recommendation model to discover
   closed consensus temporal patterns, where closed means the patterns are
   only the maximum consensus sequences. Experiments using synthetic and
   real datasets showed the model's computational efficiency, scalability,
   and effectiveness. (C) 2013 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Huang, TCK (Reprint Author), Natl Chung Cheng Univ, Dept Business Adm, 168 Univ Rd, Chiayi, Taiwan.
   Natl Chung Cheng Univ, Dept Business Adm, Chiayi, Taiwan.}},
DOI = {{10.1016/j.knosys.2013.10.003}},
ISSN = {{0950-7051}},
EISSN = {{1872-7409}},
Keywords = {{Group decision making; Data mining; Recommendation systems; Consensus
   temporal pattern; Closed pattern}},
Keywords-Plus = {{MINING SEQUENTIAL PATTERNS; INTERVAL-BASED EVENTS; TRAVERSAL PATTERNS;
   CHOICE FUNCTIONS; FUZZY; PREFERENCE; RANKING; MODEL; STRATEGIES;
   DATABASES}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{bmahck@ccu.edu.tw}},
Funding-Acknowledgement = {{National Science Council of the Republic of China {[}NSC
   101-2918-1-194-008]}},
Funding-Text = {{The author would like to thank the Editor in Chief, Dr. Jie Lu,
   Associate Editor, and two anonymous referees for their helps and
   valuable comments to improve this paper. He also appreciates Krannert
   School of Management, Purdue University, providing the research
   resources to support the revision of this paper during his visiting
   period. The assistance in the real-dataset collection and the discovery
   of its patterns by Mr. Cheng-Qi Chang is thankful as well. This research
   was supported by the National Science Council of the Republic of China
   under the Grant NSC 101-2918-1-194-008.}},
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Number-of-Cited-References = {{60}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{18}},
Journal-ISO = {{Knowledge-Based Syst.}},
Doc-Delivery-Number = {{261SV}},
Unique-ID = {{ISI:000327685800029}},
}

@article{ ISI:000209525600002,
Author = {Sampath, Srinath and Verducci, Joseph S.},
Title = {{Detecting the End of Agreement between Two Long Ranked Lists}},
Journal = {{STATISTICAL ANALYSIS AND DATA MINING}},
Year = {{2013}},
Volume = {{6}},
Number = {{6, SI}},
Pages = {{458-471}},
Month = {{DEC}},
Abstract = {{We propose an alternative approach to the problem recently posed by Hall
   and Schimek (Journal of the American Statistical Association,
   107(498)(2012), 661-672): determining at what point the agreement
   between two rankings of a long list of items degenerates into noise. We
   modify the method of estimation in Fligner and Verducci's (Journal of
   the American Statistical Association, 83(403)(1988), 892-901) multistage
   model for rankings, from maximum likelihood of conditional agreement
   over a sample of rankings to a locally smoothed estimator of agreement.
   Through simulations we show that this modification performs very well
   under several conditions. We apply our technique as a stopping rule to
   supplement the tau-path algorithm, developed by Yu et al. (Statistical
   Methodology 8(2011), 97-111), in an analysis of associations between
   gene expression and compound potency in cancer data, and discuss some
   ramifications as planned extensions. (C) 2013 Wiley Periodicals, Inc.
   Statistical Analysis and Data Mining 6: 458-471, 2013}},
Publisher = {{WILEY-BLACKWELL}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Sampath, S (Reprint Author), Ohio State Univ, Dept Stat, Columbus, OH 43210 USA.
   Sampath, Srinath; Verducci, Joseph S., Ohio State Univ, Dept Stat, Columbus, OH 43210 USA.}},
DOI = {{10.1002/sam.11205}},
ISSN = {{1932-1864}},
EISSN = {{1932-1872}},
Keywords = {{partial rankings; top-K rank list; rank aggregation; multistage model;
   maximum likelihood estimation; consensus}},
Research-Areas = {{Computer Science; Mathematics}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Computer Science,
   Interdisciplinary Applications; Statistics \& Probability}},
Author-Email = {{sampath.5@osu.edu}},
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Number-of-Cited-References = {{18}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Stat. Anal. Data Min.}},
Doc-Delivery-Number = {{V41CZ}},
Unique-ID = {{ISI:000209525600002}},
}

@article{ ISI:000327746100002,
Author = {Duchi, John C. and Mackey, Lester and Jordan, Michael I.},
Title = {{THE ASYMPTOTICS OF RANKING ALGORITHMS}},
Journal = {{ANNALS OF STATISTICS}},
Year = {{2013}},
Volume = {{41}},
Number = {{5}},
Pages = {{2292-2323}},
Month = {{OCT}},
Abstract = {{We consider the predictive problem of supervised ranking, where the task
   is to rank sets of candidate items returned in response to queries.
   Although there exist statistical procedures that come with guarantees of
   consistency in this setting, these procedures require that individuals
   provide a complete ranking of all items, which is rarely feasible in
   practice. Instead, individuals routinely provide partial preference
   information, such as pairwise comparisons of items, and more practical
   approaches to ranking have aimed at modeling this partial preference
   data directly. As we show, however, such an approach raises serious
   theoretical challenges. Indeed, we demonstrate that many commonly used
   surrogate losses for pairwise comparison data do not yield consistency;
   surprisingly, we show inconsistency even in low-noise settings. With
   these negative results as motivation, we present a new approach to
   supervised ranking based on aggregation of partial preferences, and we
   develop U-statistic-based empirical risk minimization procedures. We
   present an asymptotic analysis of these new procedures, showing that
   they yield consistency results that parallel those available for
   classification. We complement our theoretical results with an experiment
   studying the new procedures in a large-scale web-ranking task.}},
Publisher = {{INST MATHEMATICAL STATISTICS}},
Address = {{3163 SOMERSET DR, CLEVELAND, OH 44122 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Duchi, JC (Reprint Author), Univ Calif Berkeley, Dept EECS, Berkeley, CA 94720 USA.
   Duchi, John C.; Jordan, Michael I., Univ Calif Berkeley, Dept EECS, Berkeley, CA 94720 USA.
   Duchi, John C.; Jordan, Michael I., Univ Calif Berkeley, Dept Stat, Berkeley, CA 94720 USA.
   Mackey, Lester, Stanford Univ, Dept Stat, Stanford, CA 94305 USA.}},
DOI = {{10.1214/13-AOS1142}},
ISSN = {{0090-5364}},
Keywords = {{Ranking; consistency; Fisher consistency; asymptotics; rank aggregation;
   U-statistics}},
Keywords-Plus = {{CLASSIFICATION METHODS; STATISTICAL-ANALYSIS; DECISION-MAKING; MINUS 2;
   MINIMIZATION; JUDGMENT; CAPACITY; ONLINE; PLUS}},
Research-Areas = {{Mathematics}},
Web-of-Science-Categories  = {{Statistics \& Probability}},
Author-Email = {{jduchi@cs.berkeley.edu
   lmackey@stanford.edu
   jordan@stat.berkeley.edu}},
Funding-Acknowledgement = {{DARPA through the National Defense Science and Engineering Graduate
   Fellowship Program (NDSEG); U.S. Army Research Office
   {[}W911NF-11-1-0391]; U.S. Army Research Laboratory}},
Funding-Text = {{Supported by DARPA through the National Defense Science and Engineering
   Graduate Fellowship Program (NDSEG).; Supported in part by the U.S. Army
   Research Laboratory and the U.S. Army Research Office under
   contract/Grant W911NF-11-1-0391.}},
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Number-of-Cited-References = {{46}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{Ann. Stat.}},
Doc-Delivery-Number = {{262OT}},
Unique-ID = {{ISI:000327746100002}},
}

@article{ ISI:000326877300056,
Author = {Aledo, Juan A. and Gamez, Jose A. and Molina, David},
Title = {{Tackling the rank aggregation problem with evolutionary algorithms}},
Journal = {{APPLIED MATHEMATICS AND COMPUTATION}},
Year = {{2013}},
Volume = {{222}},
Pages = {{632-644}},
Month = {{OCT 1}},
Abstract = {{Probabilistic reasoning and learning with permutation data has gained
   interest in recent years because its use in different ranking-based
   real-world applications. Therefore, constructing a model from a given
   set of permutations or rankings has become a target problem in the
   machine learning community. In this paper we focus on probabilistic
   modelling and concretely in the use of a well known permutation-based
   distribution as it is the Mallows model.
   Learning a Mallows model from data requires the estimation of two
   parameters, a consensus permutation pi(0) and a dispersion parameter
   theta. Since the exact computation of these parameters is an NP-hard
   problem, it is natural to consider heuristics to tackle this problem. An
   interesting approach consists in the use of a two-step procedure, first
   estimating pi(0), and then computing theta for a given pi(0). This is
   possible because the optimal pi(0) does not depend on theta. When
   following this approach, computation of pi(0) reduces to the rank
   aggregation problem, which consists in finding the ranking which best
   represents such dataset.
   In this paper we propose to use genetic algorithms to tackle this
   problem, studying its performance with respect to state-of-the-art
   algorithms, specially in complex cases, that is, when the number of
   items to rank is large and there is few consensus between the available
   rankings (which traduces in a low value for theta).
   After a series of experiments involving data of different type, we
   conclude that our evolutionary approach clearly outperforms the
   remaining tested algorithms. (C) 2013 Elsevier Inc. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE INC}},
Address = {{360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Aledo, JA (Reprint Author), Univ Castilla La Mancha, Dept Matemat, Albacete 02071, Spain.
   Aledo, Juan A., Univ Castilla La Mancha, Dept Matemat, Albacete 02071, Spain.
   Gamez, Jose A.; Molina, David, Univ Castilla La Mancha, Dept Sistemas Informat, Albacete 02071, Spain.}},
DOI = {{10.1016/j.amc.2013.07.081}},
ISSN = {{0096-3003}},
EISSN = {{1873-5649}},
Keywords = {{Kendall distance; Mallows model; Rank aggregation; Kemeny ranking
   problem; Genetic algorithms}},
Keywords-Plus = {{TRAVELING SALESMAN PROBLEM; MODELS}},
Research-Areas = {{Mathematics}},
Web-of-Science-Categories  = {{Mathematics, Applied}},
Author-Email = {{juanangel.aledo@uclm.es
   jose.gamez@uclm.es
   d.molina@estudiante.uam.es}},
ResearcherID-Numbers = {{Gamez, Jose A./K-5098-2014
   Aledo, Juan A./N-3631-2014}},
ORCID-Numbers = {{Gamez, Jose A./0000-0003-1188-1117
   Aledo, Juan A./0000-0003-1786-8087}},
Funding-Acknowledgement = {{FEDER funds; Spanish Government (MICINN) {[}TIN2010-20900-C04-03]}},
Funding-Text = {{This paper is a wide extension of a preliminary version presented at
   IEA/AIE 2013 Conference {[}41]. The authors want to thank Alnur Ali and
   Marina Meila for facilitating us the code including their branch and
   bound implementation and the other algorithms used in the experimental
   comparison. This work has been partially funded by FEDER funds and the
   Spanish Government (MICINN) through project TIN2010-20900-C04-03.}},
Cited-References = {{Aledo J.A., 2013, LECT NOTES COMPUTER, V7906, P102.
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Number-of-Cited-References = {{41}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Appl. Math. Comput.}},
Doc-Delivery-Number = {{250TI}},
Unique-ID = {{ISI:000326877300056}},
}

@article{ ISI:000323469300070,
Author = {Muravyov, Sergey V.},
Title = {{Ordinal measurement, preference aggregation and interlaboratory
   comparisons}},
Journal = {{MEASUREMENT}},
Year = {{2013}},
Volume = {{46}},
Number = {{8}},
Pages = {{2927-2935}},
Month = {{OCT}},
Abstract = {{The classical problem of a single consensus ranking determination for m
   rankings of n alternatives has a potential of wide applications in
   information technologies, and particularly in measurement and
   instrumentation. The Kemeny rule is one of deeply justified ways to
   solve the problem allowing to find such a linear order (Kemeny ranking)
   of alternatives that a distance (defined in terms of a number of
   pair-wise disagreements between rankings) from it to the initial
   rankings is minimal. But the approach can result in considerably more
   than one optimal solutions what can reduce its applicability. By
   computational experiments outcomes, the paper demonstrates that a set of
   Kemeny rankings cardinality can be extremely large in small size cases
   (m = 4, n = 15 ... 20) and, consequently, special efforts to build an
   appropriate convoluting solution are needed. Application of the model to
   one of practical metrological problems, such as interlaboratory
   comparisons, is proposed and examined. (c) 2013 Elsevier Ltd. All rights
   reserved.}},
Publisher = {{ELSEVIER SCI LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Muravyov, SV (Reprint Author), Natl Res Tomsk Polytech Univ, Dept Comp Aided Measurement Syst \& Metrol, Pr Lenina 30, Tomsk 634050, Russia.
   Natl Res Tomsk Polytech Univ, Dept Comp Aided Measurement Syst \& Metrol, Tomsk 634050, Russia.}},
DOI = {{10.1016/j.measurement.2013.04.044}},
ISSN = {{0263-2241}},
Keywords = {{Rankings; Consensus relation; Preference aggregation; Kemeny ranking
   problem; Multiple optimal solutions; Interlaboratory comparisons}},
Keywords-Plus = {{KEY COMPARISON DATA}},
Research-Areas = {{Engineering; Instruments \& Instrumentation}},
Web-of-Science-Categories  = {{Engineering, Multidisciplinary; Instruments \& Instrumentation}},
Author-Email = {{muravyov@camsam.tpu.ru}},
ResearcherID-Numbers = {{Muravyov, Sergey/N-2896-2013}},
ORCID-Numbers = {{Muravyov, Sergey/0000-0001-5650-1400}},
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Number-of-Cited-References = {{33}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{Measurement}},
Doc-Delivery-Number = {{205UC}},
Unique-ID = {{ISI:000323469300070}},
}

@article{ ISI:000318989100009,
Author = {Yazdani, Alireza and Duenas-Osorio, Leonardo and Li, Qilin},
Title = {{A scoring mechanism for the rank aggregation of network robustness}},
Journal = {{COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION}},
Year = {{2013}},
Volume = {{18}},
Number = {{10}},
Pages = {{2722-2732}},
Month = {{OCT}},
Abstract = {{To date, a number of metrics have been proposed to quantify inherent
   robustness of network topology against failures. However, each single
   metric usually only offers a limited view of network vulnerability to
   different types of random failures and targeted attacks. When applied to
   certain network configurations, different metrics rank network topology
   robustness in different orders which is rather inconsistent, and no
   single metric fully characterizes network robustness against different
   modes of failure. To overcome such inconsistency, this work proposes a
   multi-metric approach as the basis of evaluating aggregate ranking of
   network topology robustness. This is based on simultaneous utilization
   of a minimal set of distinct robustness metrics that are standardized so
   to give way to a direct comparison of vulnerability across networks with
   different sizes and configurations, hence leading to an initial scoring
   of inherent topology robustness. Subsequently, based on the inputs of
   initial scoring a rank aggregation method is employed to allocate an
   overall ranking of robustness to each network topology. A discussion is
   presented in support of the presented multi-metric approach and its
   applications to more realistically assess and rank network topology
   robustness. (C) 2013 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Yazdani, A (Reprint Author), Rice Univ, Dept Civil \& Environm Engn, Houston, TX 77005 USA.
   Yazdani, Alireza; Duenas-Osorio, Leonardo; Li, Qilin, Rice Univ, Dept Civil \& Environm Engn, Houston, TX 77005 USA.}},
DOI = {{10.1016/j.cnsns.2013.03.002}},
ISSN = {{1007-5704}},
Keywords = {{Complex graphs; Network topology; Rank aggregation; System vulnerability}},
Keywords-Plus = {{COMPLEX NETWORKS; BETWEENNESS; CENTRALITY; GRAPHS}},
Research-Areas = {{Mathematics; Mechanics; Physics}},
Web-of-Science-Categories  = {{Mathematics, Applied; Mathematics, Interdisciplinary Applications;
   Mechanics; Physics, Fluids \& Plasmas; Physics, Mathematical}},
Author-Email = {{alireza.yazdani@rice.edu}},
ResearcherID-Numbers = {{Li, Qilin/A-8970-2008}},
ORCID-Numbers = {{Li, Qilin/0000-0001-5756-3873}},
Funding-Acknowledgement = {{Shell Center for Sustainability, Rice University (USA)}},
Funding-Text = {{This research is conducted as part of a project sponsored by the Shell
   Center for Sustainability, Rice University (USA). The authors thank the
   anonymous reviewers for their comments.}},
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Number-of-Cited-References = {{39}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{20}},
Journal-ISO = {{Commun. Nonlinear Sci. Numer. Simul.}},
Doc-Delivery-Number = {{145BV}},
Unique-ID = {{ISI:000318989100009}},
}

@article{ ISI:000326338900001,
Author = {Ma, Ming-Zhe and Kong, Xiang and Weng, Ming-Zhe and Cheng, Kun and Gong,
   Wei and Quan, Zhi-Wei and Peng, Cheng-Hong},
Title = {{Candidate microRNA biomarkers of pancreatic ductal adenocarcinoma:
   meta-analysis, experimental validation and clinical significance}},
Journal = {{JOURNAL OF EXPERIMENTAL \& CLINICAL CANCER RESEARCH}},
Year = {{2013}},
Volume = {{32}},
Month = {{SEP 28}},
Abstract = {{Background: The diagnostic and prognostic value of microRNA (miRNA)
   expression aberrations in pancreatic ductal adenocarcinoma (PDAC) has
   been studied extensively in recent years. However, differences in
   measurement platforms and lab protocols as well as small sample sizes
   can render gene expression levels incomparable.
   Methods: A comprehensive meta-review of published studies in PDAC that
   compared the miRNA expression profiles of PDAC tissues and paired
   neighbouring noncancerous pancreatic tissues was performed to determine
   candidate miRNA biomarkers for PDAC. Both a miRNA vote-counting strategy
   and a recently published Robust Rank Aggregation method were employed.
   In this review, a total of 538 tumour and 206 noncancerous control
   samples were included.
   Results: We identified a statistically significant miRNA meta-signature
   of seven up and three down-regulated miRNAs. The experimental validation
   results showed that the miRNA expression levels were in accordance with
   the meta-signature. The results from the vote-counting strategy were
   consistent with those from the Robust Rank Aggregation method. The
   experimental validation confirmed that the statistically unique profiles
   identified by the meta-review approach could discriminate PDAC tissues
   from paired nonmalignant pancreatic tissues. In a cohort of 70 patients,
   the high expression of miR-21 (p=0.018, HR=2.610; 95\% CI=1.179-5.777)
   and miR-31 (p=0.039, HR=2.735; 95\% CI=1.317-6.426), the low expression
   of miR-375 (p=0.022, HR=2.337; 95\% CI=1.431-5.066) were associated with
   poor overall survival following resection, independent of clinical
   covariates.
   Conclusions: The identified miRNAs may be used to develop a panel of
   diagnostic and prognostic biomarkers for PDAC with sufficient
   sensitivity and specificity for use in a clinical setting.}},
Publisher = {{BIOMED CENTRAL LTD}},
Address = {{236 GRAYS INN RD, FLOOR 6, LONDON WC1X 8HL, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Gong, W (Reprint Author), Shanghai Jiao Tong Univ, Sch Med, Xinhua Hosp, Dept Gen Surg, 1665 Kongjiang Rd, Shanghai 200092, Peoples R China.
   Ma, Ming-Zhe; Weng, Ming-Zhe; Gong, Wei; Quan, Zhi-Wei, Shanghai Jiao Tong Univ, Sch Med, Xinhua Hosp, Dept Gen Surg, Shanghai 200092, Peoples R China.
   Kong, Xiang, Shanghai Jiao Tong Univ, Sch Med, Xinhua Hosp, Dept Endocrinol, Shanghai 200092, Peoples R China.
   Cheng, Kun; Peng, Cheng-Hong, Shanghai Jiao Tong Univ, Sch Med, Ruijin Hosp, Dept Gen Surg, Shanghai 200092, Peoples R China.}},
DOI = {{10.1186/1756-9966-32-71}},
Article-Number = {{71}},
ISSN = {{1756-9966}},
Keywords = {{microRNA; Meta-analysis; Pancreatic cancer; Biomarker}},
Keywords-Plus = {{GENE-EXPRESSION; LUNG-CANCER; MICROARRAY; DIAGNOSIS; PATTERNS; SURVIVAL;
   TARGETS; TISSUES; PCR}},
Research-Areas = {{Oncology}},
Web-of-Science-Categories  = {{Oncology}},
Author-Email = {{gongweius@hotmail.com
   zhiwquan@163.com}},
Funding-Acknowledgement = {{National Natural Science Foundation of China {[}81272747]}},
Funding-Text = {{This work was supported by National Natural Science Foundation of China
   (grant no. 81272747). The funding sources had no role in the study
   design, data collection, analysis or interpretation, or the writing of
   this manuscript. The authors thank the Department of General Surgery of
   Ruijin Hospital for providing the PDAC tissue samples and Dr. Fei Yuan
   for the pathology assessments.}},
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Number-of-Cited-References = {{42}},
Times-Cited = {{21}},
Usage-Count-(Last-180-days) = {{7}},
Usage-Count-Since-2013 = {{22}},
Journal-ISO = {{J. Exp. Clin. Cancer Res.}},
Doc-Delivery-Number = {{243SX}},
Unique-ID = {{ISI:000326338900001}},
}

@article{ ISI:000324405200014,
Author = {Osting, Braxton and Darbon, Jerome and Osher, Stanley},
Title = {{STATISTICAL RANKING USING THE l(1)-NORM ON GRAPHS}},
Journal = {{INVERSE PROBLEMS AND IMAGING}},
Year = {{2013}},
Volume = {{7}},
Number = {{3, SI}},
Pages = {{907-926}},
Month = {{AUG}},
Abstract = {{We consider the problem of establishing a statistical ranking for a set
   of alternatives from a dataset which consists of an (inconsistent and
   incomplete) set of quantitative pairwise comparisons of the
   alternatives. If we consider the directed graph where vertices represent
   the alternatives and the pairwise comparison data is a function on the
   arcs, then the statistical ranking problem is to find a potential
   function, defined on the vertices, such that the gradient of the
   potential optimally agrees with the pairwise comparisons. Potentials,
   optimal in the l(2)-norm sense, can be found by solving a least-squares
   problem on the digraph and, recently, the residual has been interpreted
   using the Hodge decomposition (Jiang et. al., 2010). In this work, we
   consider an l(1)-norm formulation of the statistical ranking problem. We
   describe a fast graph-cut approach for finding epsilon-optimal
   solutions, which has been used successfully in image processing and
   computer vision problems. Applying this method to several datasets, we
   demonstrate its efficacy at finding solutions with sparse residual.}},
Publisher = {{AMER INST MATHEMATICAL SCIENCES}},
Address = {{PO BOX 2604, SPRINGFIELD, MO 65801-2604 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Osting, B (Reprint Author), Univ Calif Los Angeles, Dept Math, Los Angeles, CA 90095 USA.
   Osting, Braxton; Darbon, Jerome; Osher, Stanley, Univ Calif Los Angeles, Dept Math, Los Angeles, CA 90095 USA.
   Darbon, Jerome, PRES UniverSud, CNRS, ENS Cachan, CMLA, F-94235 Cachan, France.}},
DOI = {{10.3934/ipi.2013.7.907}},
ISSN = {{1930-8337}},
EISSN = {{1930-8345}},
Keywords = {{Statistical ranking; rank aggregation; Kemeny-Snell ordering; HodgeRank;
   l(1)-norm minimization; graph-cut method}},
Keywords-Plus = {{ENERGY MINIMIZATION; ORDINAL RANKING; CUTS; PREFERENCE; INTENSITY;
   FOOTBALL; MODEL}},
Research-Areas = {{Mathematics; Physics}},
Web-of-Science-Categories  = {{Mathematics, Applied; Physics, Mathematical}},
Author-Email = {{braxton@math.ucla.edu
   jerome@math.ucla.edu
   sjo@math.ucla.edu}},
Funding-Acknowledgement = {{NSF {[}DMS-1103959, DMS-0914561]; ONR {[}N00014-08-1-1119,
   N00014-10-0221];  {[}ONR-N00014-11-1-0749]}},
Funding-Text = {{We thank Yuan Yao for suggesting this problem and Lawrence Carin for
   directing us to the Yahoo! Webscope dataset. Finally, we thank the
   referees for their helpful comments. B. Osting is supported by NSF
   DMS-1103959. J. Darbon is supported by ONR-N00014-11-1-0749. S. Osher is
   supported by ONR N00014-08-1-1119, N00014-10-0221, and NSF DMS-0914561.}},
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Number-of-Cited-References = {{38}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{Inverse Probl. Imaging}},
Doc-Delivery-Number = {{218AO}},
Unique-ID = {{ISI:000324405200014}},
}

@article{ ISI:000323125600004,
Author = {Bandyopadhyay, Sanghamitra and Sengupta, Debarka and Maulik, Ujjwal},
Title = {{GRF: A Greedy Rank Fusion Algorithm for Combining MicroRNA Target
   Orderings}},
Journal = {{MOLECULAR INFORMATICS}},
Year = {{2013}},
Volume = {{32}},
Number = {{8}},
Pages = {{685-691}},
Month = {{AUG}},
Publisher = {{WILEY-V C H VERLAG GMBH}},
Address = {{POSTFACH 101161, 69451 WEINHEIM, GERMANY}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Bandyopadhyay, S (Reprint Author), Indian Stat Inst, Machine Intelligence Unit, Kolkata 700108, India.
   Bandyopadhyay, Sanghamitra; Sengupta, Debarka, Indian Stat Inst, Machine Intelligence Unit, Kolkata 700108, India.
   Maulik, Ujjwal, Jadavpur Univ, Dept Comp Sci \& Engn, Kolkata 700032, India.}},
DOI = {{10.1002/minf.201200165}},
ISSN = {{1868-1743}},
EISSN = {{1868-1751}},
Keywords = {{MicroRNA; mRNA; Target; Greedy; Rank aggregation}},
Keywords-Plus = {{PREDICTION; IDENTIFICATION; AGGREGATION; INTEGRATION}},
Research-Areas = {{Pharmacology \& Pharmacy; Computer Science; Mathematical \&
   Computational Biology}},
Web-of-Science-Categories  = {{Chemistry, Medicinal; Computer Science, Interdisciplinary Applications;
   Mathematical \& Computational Biology}},
Author-Email = {{sanghami@isical.ac.in
   umaulik@cse.jdvu.ac.in}},
Funding-Acknowledgement = {{Department of Science and Technology, Government of India
   {[}DST/SJF/ET-02/2006-07]; DST {[}DST/INT/CP-STIO/2007-2008(40)/2008]}},
Funding-Text = {{D.S. and S.B. gratefully acknowledge the financial support from the
   Grant no. DST/SJF/ET-02/2006-07 under the Swarnajayanti Fellowship
   Scheme of the Department of Science and Technology, Government of India.
   S. B also acknowledges DST Grant No. DST/INT/CP-STIO/2007-2008(40)/2008.}},
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Number-of-Cited-References = {{23}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{Mol. Inf.}},
Doc-Delivery-Number = {{201FH}},
Unique-ID = {{ISI:000323125600004}},
}

@article{ ISI:000321062500007,
Author = {Brandenburg, Franz J. and Gleissner, Andreas and Hofmeier, Andreas},
Title = {{The nearest neighbor Spearman footrule distance for bucket, interval,
   and partial orders}},
Journal = {{JOURNAL OF COMBINATORIAL OPTIMIZATION}},
Year = {{2013}},
Volume = {{26}},
Number = {{2, SI}},
Pages = {{310-332}},
Month = {{AUG}},
Abstract = {{Comparing and ranking information is an important topic in social and
   information sciences, and in particular on the web. Its objective is to
   measure the difference of the preferences of voters on a set of
   candidates and to compute a consensus ranking. Commonly, each voter
   provides a total order of all candidates. Recently, this approach was
   generalized to bucket orders, which allow ties.
   In this work we further generalize and consider total, bucket, interval
   and partial orders. The disagreement between two orders is measured by
   the nearest neighbor Spearman footrule distance, which has not been
   studied so far. For two bucket orders and for a total and an interval
   order the nearest neighbor Spearman footrule distance is shown to be
   computable in linear time, whereas for a total and a partial order the
   computation is NP-hard, 4-approximable and fixed-parameter tractable.
   Moreover, in contrast to the well-known efficient solution of the rank
   aggregation problem for total orders, we prove the NP-completeness for
   bucket orders and establish a 4-approximation.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Gleissner, A (Reprint Author), Univ Passau, Fac Comp Sci \& Math, D-94030 Passau, Germany.
   Brandenburg, Franz J.; Gleissner, Andreas; Hofmeier, Andreas, Univ Passau, Fac Comp Sci \& Math, D-94030 Passau, Germany.}},
DOI = {{10.1007/s10878-012-9467-x}},
ISSN = {{1382-6905}},
Keywords = {{Ranking; Rank aggregation; Partial orders; Spearman footrule distance;
   Fixed-parameter tractability}},
Research-Areas = {{Computer Science; Mathematics}},
Web-of-Science-Categories  = {{Computer Science, Interdisciplinary Applications; Mathematics, Applied}},
Author-Email = {{brandenb@fim.uni-passau.de
   gleissner@fim.uni-passau.de
   hofmeier@fim.uni-passau.de}},
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Number-of-Cited-References = {{28}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{J. Comb. Optim.}},
Doc-Delivery-Number = {{173FC}},
Unique-ID = {{ISI:000321062500007}},
}

@article{ ISI:000317944800024,
Author = {Guimaraes Pedronette, Daniel Carlos and Torres, Ricardo da S.},
Title = {{Image re-ranking and rank aggregation based on similarity of ranked
   lists}},
Journal = {{PATTERN RECOGNITION}},
Year = {{2013}},
Volume = {{46}},
Number = {{8}},
Pages = {{2350-2360}},
Month = {{AUG}},
Abstract = {{In Content-based Image Retrieval (CBIR) systems, ranking accurately
   collection images is of great relevance. Users are interested in the
   returned images placed at the first positions, which usually are the
   most relevant ones. Collection images are ranked in increasing order of
   their distance to the query pattern (e.g., query image) defined by
   users. Therefore, the effectiveness of these systems is very dependent
   on the accuracy of the distance function adopted. In this paper, we
   present a novel context-based approach for redefining distances and
   later re-ranking images aiming to improve the effectiveness of CBIR
   systems. In our approach, distances among images are redefined based on
   the similarity of their ranked lists. Conducted experiments involving
   shape, color, and texture descriptors demonstrate the effectiveness of
   our method. (C) 2013 Elsevier Ltd. All rights reserved.}},
Publisher = {{ELSEVIER SCI LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Pedronette, DCG (Reprint Author), Univ Campinas UNICAMP, RECOD Lab, Inst Comp IC, Campinas, SP, Brazil.
   Guimaraes Pedronette, Daniel Carlos; Torres, Ricardo da S., Univ Campinas UNICAMP, RECOD Lab, Inst Comp IC, Campinas, SP, Brazil.}},
DOI = {{10.1016/j.patcog.2013.01.004}},
ISSN = {{0031-3203}},
Keywords = {{Content-based image retrieval; Re-ranking; Ranked lists; Rank
   aggregation}},
Keywords-Plus = {{NONLINEAR DIMENSIONALITY REDUCTION; EXPLOITING CONTEXTUAL INFORMATION;
   SHAPE RETRIEVAL; RECOGNITION; DISTANCE; CLASSIFICATION; TRANSDUCTION;
   DESCRIPTORS; CONTOUR}},
Research-Areas = {{Computer Science; Engineering}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Engineering, Electrical \&
   Electronic}},
Author-Email = {{dcarlos@ic.unicamp.br
   rtorres@ic.unicamp.br}},
ResearcherID-Numbers = {{Pedronette, Daniel/E-7817-2015}},
Funding-Acknowledgement = {{AMD; CAPES; FAPESP; FAEPEX; CNPq; DGA/UNICAMP}},
Funding-Text = {{Authors thank AMD, CAPES, FAPESP, FAEPEX, and CNPq for financial
   support. Authors also thank DGA/UNICAMP for its support in this work.}},
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Number-of-Cited-References = {{47}},
Times-Cited = {{8}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{30}},
Journal-ISO = {{Pattern Recognit.}},
Doc-Delivery-Number = {{130UE}},
Unique-ID = {{ISI:000317944800024}},
}

@article{ ISI:000322242400020,
Author = {Ivanov, S. V. and Panaccione, A. and Nonaka, D. and Prasad, M. L. and
   Boyd, K. L. and Brown, B. and Guo, Y. and Sewell, A. and Yarbrough, W.
   G.},
Title = {{Diagnostic SOX10 gene signatures in salivary adenoid cystic and breast
   basal-like carcinomas}},
Journal = {{BRITISH JOURNAL OF CANCER}},
Year = {{2013}},
Volume = {{109}},
Number = {{2}},
Pages = {{444-451}},
Month = {{JUL 23}},
Abstract = {{Background: Salivary adenoid cystic carcinoma (ACC) is an insidious
   slow-growing cancer with the propensity to recur and metastasise to
   distant sites. Basal-like breast carcinoma (BBC) is a molecular subtype
   that constitutes 15-20\% of breast cancers, shares histological
   similarities and basal cell markers with ACC, lacks expression of ER
   (oestrogen receptor), PR (progesterone receptor), and HER2 (human
   epidermal growth factor receptor 2), and, similar to ACC, metastasises
   predominantly to the lung and brain. Both cancers lack targeted
   therapies owing to poor understanding of their molecular drivers.
   Methods: Gene expression profiling, immunohistochemical staining,
   western blot, RT-PCR, and in silico analysis of massive cancer data sets
   were used to identify novel markers and potential therapeutic targets
   for ACC and BBC. For the detection and comparison of gene signatures, we
   performed co-expression analysis using a recently developed web-based
   multi-experiment matrix tool for visualisation and rank aggregation.
   Results: In ACC and BBC we identified characteristic and overlapping
   SOX10 gene signatures that contained a large set of novel potential
   molecular markers. SOX10 was validated as a sensitive diagnostic marker
   for both cancers and its expression was linked to normal and malignant
   myoepithelial/basal cells. In ACC, BBC, and melanoma (MEL), SOX10
   expression strongly co-segregated with the expression of ROPN1B, GPM6B,
   COL9A3, and MIA. In ACC and breast cancers, SOX10 expression negatively
   correlated with FOXA1, a cell identity marker and major regulator of the
   luminal breast subtype. Diagnostic significance of several conserved
   elements of the SOX10 signature (MIA, TRIM2, ROPN1, and ROPN1B) was
   validated on BBC cell lines.
   Conclusion: SOX10 expression in ACC and BBC appears to be a part of a
   highly coordinated transcriptional programme characteristic for cancers
   with basal/myoepithelial features. Comparison between ACC/BBC and other
   cancers, such as neuroblastomaand MEL, reveals potential molecular
   markers specific for these cancers that are likely linked to their cell
   identity. SOX10 as a novel diagnostic marker for ACC and BBC provides
   important molecular insight into their molecular aetiology and cell
   origin. Given that SOX10 was recently described as a principal driver of
   MEL, identification of conserved elements of the SOX10 signatures may
   help in better understanding of SOX10-related signalling and development
   of novel diagnostic and therapeutic tools.}},
Publisher = {{NATURE PUBLISHING GROUP}},
Address = {{MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ivanov, SV (Reprint Author), Yale Univ, Sch Med, Dept Surg, Otolaryngol Sect, Yale Phys Bldg,800 Howard Ave,4th Floor, New Haven, CT 06519 USA.
   Ivanov, S. V.; Panaccione, A.; Sewell, A.; Yarbrough, W. G., Yale Univ, Sch Med, Dept Surg, Otolaryngol Sect, New Haven, CT 06519 USA.
   Panaccione, A., Vanderbilt Univ, Sch Med, Dept Canc Biol, Nashville, TN 37212 USA.
   Nonaka, D., Christie NHS Fdn Trust, Univ Manchester, Sch Med, Dept Histopathol, Manchester, Lancs, England.
   Prasad, M. L., Yale Univ, Sch Med, Dept Pathol, New Haven, CT 06519 USA.
   Boyd, K. L., Vanderbilt Univ, Med Ctr, Dept Pathol, Nashville, TN 37232 USA.
   Brown, B., Vanderbilt Univ, Sch Med, Dept Otolaryngol, Nashville, TN 37212 USA.
   Brown, B., Vanderbilt Univ, Sch Med, Barry Baker Lab Head \& Neck Oncol Vanderbilt, Nashville, TN 37212 USA.
   Guo, Y., Vanderbilt Univ, Sch Med, Dept Biomed Informat, Nashville, TN 37212 USA.
   Yarbrough, W. G., Smilow Canc Hosp, H\&N Dis Ctr, New Haven, CT USA.
   Yarbrough, W. G., Yale Univ, Ctr Canc, Mol Virol Program, New Haven, CT 06519 USA.}},
DOI = {{10.1038/bjc.2013.326}},
ISSN = {{0007-0920}},
Keywords = {{SOX10; salivary adenoid cystic carcinoma; basal-like breast carcinoma;
   melanoma; neural stem markers}},
Keywords-Plus = {{TRANSCRIPTION FACTOR SOX10; HIRSCHSPRUNG-DISEASE; CELL-MIGRATION; RANK
   AGGREGATION; CANCER; EXPRESSION; MELANOMA; PROTEIN; TUMORS; FOXA1}},
Research-Areas = {{Oncology}},
Web-of-Science-Categories  = {{Oncology}},
Author-Email = {{sergey.ivanov@yale.edu
   wendell.yarbrough@yale.edu}},
Funding-Acknowledgement = {{Adenoid Cystic Carcinoma Research Foundation; National Institute of
   Dental and Craniofacial Research {[}1RC1DE020332-01]; Department of
   Surgery, Yale School of Medicine; Vanderbilt Ingram Cancer Center;
   Vanderbilt Bill Wilkerson Center for Otolaryngology and Communication
   Sciences; Robert J Kleberg Jr and Helen C Kleberg Foundation; NIH Office
   of Rare Diseases Research {[}U01DE019765]; NYULCI Center {[}NIH/NCI 5
   P30CA16087-31]}},
Funding-Text = {{This study was supported by funds from the Adenoid Cystic Carcinoma
   Research Foundation to SI and WGY, and by grant number 1RC1DE020332-01
   from the National Institute of Dental and Craniofacial Research to WGY.
   This work was also supported in part by funds from the Department of
   Surgery, Yale School of Medicine, and the Vanderbilt Ingram Cancer
   Center, the Vanderbilt Bill Wilkerson Center for Otolaryngology and
   Communication Sciences, the Robert J Kleberg Jr and Helen C Kleberg
   Foundation, and by an endowment to the Barry Baker Laboratory for Head
   and Neck Oncology. We acknowledge Dr Adel El-Naggar (MD Anderson Cancer
   Center) and the NIH National Institute of Dental and Craniofacial
   Research and the NIH Office of Rare Diseases Research grant number
   U01DE019765 (PI, Adel El-Naggar) for providing useful discussion and
   tumour specimens. Authors are grateful to Dr. Luis A Chiriboga and
   Stephanie A Krauter for help with IHC staining. The Experimental
   Pathology and Immunohistochemistry core laboratory is supported in part
   by NYULCI Center Support Grant NIH/NCI 5 P30CA16087-31.}},
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Number-of-Cited-References = {{51}},
Times-Cited = {{11}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{Br. J. Cancer}},
Doc-Delivery-Number = {{189BQ}},
Unique-ID = {{ISI:000322242400020}},
}

@article{ ISI:000317593100018,
Author = {Vosa, Urmo and Vooder, Tonu and Kolde, Raivo and Vilo, Jaak and
   Metspalu, Andres and Annilo, Tarmo},
Title = {{Meta-analysis of microRNA expression in lung cancer}},
Journal = {{INTERNATIONAL JOURNAL OF CANCER}},
Year = {{2013}},
Volume = {{132}},
Number = {{12}},
Pages = {{2884-2893}},
Month = {{JUN 15}},
Abstract = {{The prognostic and diagnostic value of microRNA (miRNA) expression
   aberrations in lung cancer has been studied intensely in recent years.
   However, due to the application of different technological platforms and
   small sample size, the miRNA expression profiling efforts have led to
   inconsistent results between the studies. We performed a comprehensive
   meta-analysis of 20 published miRNA expression studies in lung cancer,
   including a total of 598 tumor and 528 non-cancerous control samples.
   Using a recently published robust rank aggregation method, we identified
   a statistically significant miRNA meta-signature of seven upregulated
   (miR-21, miR-210, miR-182, miR-31, miR-200b, miR-205 and miR-183) and
   eight downregulated (miR-126-3p, miR-30a, miR-30d, miR-486-5p, miR-451a,
   miR-126-5p, miR-143 and miR-145) miRNAs. We conducted a gene set
   enrichment analysis to identify pathways that are most strongly affected
   by altered expression of these miRNAs. We found that meta-signature
   miRNAs cooperatively target functionally related and biologically
   relevant genes in signaling and developmental pathways. We have shown
   that such meta-analysis approach is suitable and effective solution for
   identification of statistically significant miRNA meta-signature by
   combining several miRNA expression studies. This method allows the
   analysis of data produced by different technological platforms that
   cannot be otherwise directly compared or in the case when raw data are
   unavailable.}},
Publisher = {{WILEY-BLACKWELL}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Annilo, T (Reprint Author), Univ Tartu, Inst Mol \& Cell Biol, Dept Biotechnol, Riia 23, EE-51010 Tartu, Estonia.
   Vosa, Urmo; Metspalu, Andres; Annilo, Tarmo, Univ Tartu, Inst Mol \& Cell Biol, Dept Biotechnol, EE-51010 Tartu, Estonia.
   Vooder, Tonu, Tartu Univ Hosp, Clin Cardiovasc \& Thorac Surg, EE-51014 Tartu, Estonia.
   Kolde, Raivo; Vilo, Jaak, Univ Tartu, Inst Comp Sci, EE-50409 Tartu, Estonia.
   Metspalu, Andres, Univ Tartu, Estonian Genome Ctr, EE-50410 Tartu, Estonia.}},
DOI = {{10.1002/ijc.27981}},
ISSN = {{0020-7136}},
EISSN = {{1097-0215}},
Keywords = {{microRNA; meta-analysis; gene set enrichment analysis; lung cancer}},
Keywords-Plus = {{SQUAMOUS-CELL CARCINOMA; NEVER-SMOKERS; PREDICTS SURVIVAL;
   MESSENGER-RNA; PROGNOSIS; SIGNATURE; TARGETS; ADENOCARCINOMAS;
   AMPLIFICATION; INTEGRATION}},
Research-Areas = {{Oncology}},
Web-of-Science-Categories  = {{Oncology}},
Author-Email = {{tarmo.annilo@ut.ee}},
ResearcherID-Numbers = {{Annilo, Tarmo/J-2900-2013
   Vilo, Jaak/A-7183-2008
   }},
ORCID-Numbers = {{Vilo, Jaak/0000-0001-5604-4107
   Kolde, Raivo/0000-0003-2886-6298}},
Funding-Acknowledgement = {{European Union through European Regional Development Fund, Centre of
   Excellence in Genomics {[}245536 OpenGene]; Estonian Ministry of
   Education and Science {[}SF0180142s08]; Estonian Science Foundation
   {[}7473]; Development Fund of the University of Tartu {[}SP1GVARENG]}},
Funding-Text = {{Grant sponsor: European Union through European Regional Development
   Fund, Centre of Excellence in Genomics and FP7 project 245536 OpenGene.
   Grant sponsor: Estonian Ministry of Education and Science; Grant number:
   SF0180142s08; Grant sponsor: Estonian Science Foundation; Grant number:
   7473; Grant sponsor: Development Fund of the University of Tartu; Grant
   number: SP1GVARENG}},
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Number-of-Cited-References = {{50}},
Times-Cited = {{62}},
Usage-Count-(Last-180-days) = {{11}},
Usage-Count-Since-2013 = {{103}},
Journal-ISO = {{Int. J. Cancer}},
Doc-Delivery-Number = {{126DV}},
Unique-ID = {{ISI:000317593100018}},
}

@article{ ISI:000319439500002,
Author = {Patel, Trina and Telesca, Donatello and Rallo, Robert and George, Saji
   and Xia, Tian and Nel, Andre E.},
Title = {{Hierarchical Rank Aggregation with Applications to Nanotoxicology}},
Journal = {{JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS}},
Year = {{2013}},
Volume = {{18}},
Number = {{2}},
Pages = {{159-177}},
Month = {{JUN}},
Abstract = {{The development of high throughput screening (HTS) assays in the field
   of nanotoxicology provide new opportunities for the hazard assessment
   and ranking of engineered nanomaterials (ENMs). It is often necessary to
   rank lists of materials based on multiple risk assessment parameters,
   often aggregated across several measures of toxicity and possibly
   spanning an array of experimental platforms. Bayesian models coupled
   with the optimization of loss functions have been shown to provide an
   effective framework for conducting inference on ranks. In this article
   we present various loss-function-based ranking approaches for comparing
   ENM within experiments and toxicity parameters. Additionally, we propose
   a framework for the aggregation of ranks across different sources of
   evidence while allowing for differential weighting of this evidence
   based on its reliability and importance in risk ranking. We apply these
   methods to high throughput toxicity data on two human cell-lines,
   exposed to eight different nanomaterials, and measured in relation to
   four cytotoxicity outcomes. This article has supplementary material
   online.}},
Publisher = {{SPRINGER}},
Address = {{233 SPRING ST, NEW YORK, NY 10013 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Patel, T (Reprint Author), Univ Calif Los Angeles, Fielding Sch Publ Hlth, Dept Biostat, 650 Charles E Young Dr South, Los Angeles, CA 90095 USA.
   Patel, Trina; Telesca, Donatello, Univ Calif Los Angeles, Fielding Sch Publ Hlth, Dept Biostat, Los Angeles, CA 90095 USA.
   Patel, Trina; Telesca, Donatello; Rallo, Robert; George, Saji; Xia, Tian, UC CEIN, Los Angeles, CA 90095 USA.
   Rallo, Robert, Univ Rovira \& Virgili, Dep Engn Informat \& Matemat, Tarragona 43007, Catalunya, Spain.
   Nel, Andre E., Univ Calif Los Angeles, Sch Med, Los Angeles, CA 90095 USA.}},
DOI = {{10.1007/s13253-013-0129-y}},
ISSN = {{1085-7117}},
Keywords = {{Bayesian hierarchical models; Hazard ranking; Loss functions;
   Nanotoxicology}},
Keywords-Plus = {{RANDOM LINEAR EXTENSIONS; CHEMICAL-SUBSTANCES; RISK-ASSESSMENT; MODELS;
   NANOTECHNOLOGY; TOXICITY; 2-STAGE; SAFETY}},
Research-Areas = {{Life Sciences \& Biomedicine - Other Topics; Mathematical \&
   Computational Biology; Mathematics}},
Web-of-Science-Categories  = {{Biology; Mathematical \& Computational Biology; Statistics \&
   Probability}},
Author-Email = {{trpatel@ucla.edu}},
ResearcherID-Numbers = {{Nel, Andre/J-2808-2012
   Geracitano, Laura/E-6926-2013
   xia, tian/C-3158-2013
   Rallo, Robert/F-4703-2010}},
ORCID-Numbers = {{xia, tian/0000-0003-0123-1305
   George, Saji/0000-0002-8807-0737
   Rallo, Robert/0000-0003-3812-4458}},
Funding-Acknowledgement = {{U.S. Public Health Service {[}U19 ES019528]; National Science
   Foundation; Environmental Protection Agency {[}DBI-0830117]}},
Funding-Text = {{Primary support was provided by the U.S. Public Health Service Grant U19
   ES019528 (UCLA Center for Nanobiology and Predictive Toxicology). This
   work was also supported by the National Science Foundation and the
   Environmental Protection Agency under Cooperative Agreement Number
   DBI-0830117. Any opinions, findings, conclusions or recommendations
   expressed herein are those of the author(s) and do not necessarily
   reflect the views of the National Science Foundation or the
   Environmental Protection Agency. This work has not been subjected to an
   EPA peer and policy review.}},
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Number-of-Cited-References = {{31}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{7}},
Usage-Count-Since-2013 = {{25}},
Journal-ISO = {{J. Agric. Biol. Environ. Stat.}},
Doc-Delivery-Number = {{151CZ}},
Unique-ID = {{ISI:000319439500002}},
}

@article{ ISI:000319358000011,
Author = {Liu, Zheng and Ge, Xiao-Xia and Wu, Xiao-Meng and Kou, Shu-Jun and Chai,
   Li-Jun and Guo, Wen-Wu},
Title = {{Selection and validation of suitable reference genes for mRNA qRT-PCR
   analysis using somatic embryogenic cultures, floral and vegetative
   tissues in citrus}},
Journal = {{PLANT CELL TISSUE AND ORGAN CULTURE}},
Year = {{2013}},
Volume = {{113}},
Number = {{3}},
Pages = {{469-481}},
Month = {{JUN}},
Abstract = {{Accuracy of the quantitative real-time reverse transcription-PCR
   (qRT-PCR) depends on the stability of the reference gene(s), i.e.
   housekeeping gene(s) used for data normalization. Recent studies have
   shown that the expression of common reference genes can vary
   considerably in certain experimental conditions. However, reference
   genes of qRT-PCR in fruit trees have not been well identified. In this
   study, stability of expression of ten potential reference genes in
   citrus, including CitACT7, CiteIF-1A, CiteIF4 alpha, CitHistone H3,
   CitHistone H4, CitTUA3, CitTUB8, CitUBL5, CitUBQ1 and CitUBQ14 was
   assessed. Furthermore, this was validated by qRT-PCR in diverse sets of
   biological samples, including embryonic callus at seven stages, embryos
   maintained at three different temperatures, five distinct plant organs,
   four floral tissues and four stages of flower development. Three
   distinct statistical algorithms, geNorm, NormFinder and Bestkeeper, were
   used to evaluate the expression stability of the candidate reference
   genes. The three outputs were merged by means of a non-weighted
   unsupervised rank aggregation method. GeNorm was also used to determine
   both the optimal number and the best combination of reference genes for
   each experimental set. The expression of CitUBQ1 was the most stable one
   across the set of all samples, flower developmental stages and somatic
   embryogenesis process under two conditions i.e. different temperature
   treatment and normal temperature treatment. CitUBQ14 presented more
   stable expression in different plant organs and floral tissues.
   CitHistone H3 was the most unsuitable reference gene in many citrus
   sample sets. In addition, the relative gene expression profile of citrus
   receptor-like kinase gene CitSERK1-like was conducted to confirm the
   validity of the reference genes in this study. Taken together, this
   study identified the reference genes that are most suitable for
   normalizing the gene expression data in citrus. These results provide
   guidelines for the selection of reference gene(s) under different
   experimental conditions, and will benefit future research on more
   accurate gene expression studies in a wide variety of samples in citrus.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Guo, WW (Reprint Author), Huazhong Agr Univ, Key Lab Hort Plant Biol, Minist Educ, Wuhan 430070, Peoples R China.
   Liu, Zheng; Ge, Xiao-Xia; Wu, Xiao-Meng; Kou, Shu-Jun; Chai, Li-Jun; Guo, Wen-Wu, Huazhong Agr Univ, Key Lab Hort Plant Biol, Minist Educ, Wuhan 430070, Peoples R China.}},
DOI = {{10.1007/s11240-013-0288-0}},
ISSN = {{0167-6857}},
Keywords = {{Citrus; qRT-PCR; Reference gene; Validation}},
Keywords-Plus = {{TIME RT-PCR; POLYMERASE-CHAIN-REACTION; CANDIDATUS
   LIBERIBACTER-ASIATICUS; VALENCIA SWEET ORANGE; SINENSIS L. OSBECK;
   HOUSEKEEPING GENES; INTERNAL CONTROL; MOLECULAR CHARACTERIZATION;
   EXPRESSION NORMALIZATION; TRIFOLIATE ORANGE}},
Research-Areas = {{Biotechnology \& Applied Microbiology; Plant Sciences}},
Web-of-Science-Categories  = {{Biotechnology \& Applied Microbiology; Plant Sciences}},
Author-Email = {{guoww@mail.hzau.edu.cn}},
Funding-Acknowledgement = {{Ministry of Science \& Technology of China {[}2011CB100606,
   2011AA100205]; National NSF of China; Ministry of Agriculture of China
   {[}200903044]}},
Funding-Text = {{This research was financially supported by the Ministry of Science \&
   Technology of China (nos. 2011CB100606, 2011AA100205), the National NSF
   of China, and the Ministry of Agriculture of China (no. 200903044).}},
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Number-of-Cited-References = {{54}},
Times-Cited = {{14}},
Usage-Count-(Last-180-days) = {{5}},
Usage-Count-Since-2013 = {{39}},
Journal-ISO = {{Plant Cell Tissue Organ Cult.}},
Doc-Delivery-Number = {{149YT}},
Unique-ID = {{ISI:000319358000011}},
}

@article{ ISI:000326552800017,
Author = {Sengupta, Debarka and Pyne, Aroonalok and Maulik, Ujjwal and
   Bandyopadhyay, Sanghamitra},
Title = {{Reformulated Kemeny Optimal Aggregation with Application in Consensus
   Ranking of microRNA Targets}},
Journal = {{IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS}},
Year = {{2013}},
Volume = {{10}},
Number = {{3}},
Pages = {{742-751}},
Month = {{MAY-JUN}},
Abstract = {{MicroRNAs are very recently discovered small noncoding RNAs, responsible
   for negative regulation of gene expression. Members of this endogenous
   family of small RNA molecules have been found implicated in many genetic
   disorders. Each microRNA targets tens to hundreds of genes. Experimental
   validation of target genes is a time- and cost-intensive procedure.
   Therefore, prediction of microRNA targets is a very important problem in
   computational biology. Though, dozens of target prediction algorithms
   have been reported in the past decade, they disagree significantly in
   terms of target gene ranking (based on predicted scores). Rank
   aggregation is often used to combine multiple target orderings suggested
   by different algorithms. This technique has been used in diverse fields
   including social choice theory, meta search in web, and most recently,
   in bioinformatics. Kemeny optimal aggregation (KOA) is considered the
   more profound objective for rank aggregation. The consensus ordering
   obtained through Kemeny optimal aggregation incurs minimum pairwise
   disagreement with the input orderings. Because of its computational
   intractability, heuristics are often formulated to obtain a near optimal
   consensus ranking. Unlike its real time use in meta search, there are a
   number of scenarios in bioinformatics (e.g., combining microRNA target
   rankings, combining disease-related gene rankings obtained froth
   microarray experiments) where evolutionary approaches can be afforded
   with the ambition of better optimization. We conjecture that an ideal
   consensus ordering should have its total disagreement shared, as equally
   as possible, with the input orderings. This is also important to refrain
   the evolutionary processes from getting stuck to local extremes. In the
   current work, we reformulate Kemeny optimal aggregation while
   introducing a trade-off between the total pairwise disagreement and its
   distribution: A simulated annealing-based implementation of the proposed
   objective has been found effective in context of microRNA target
   ranking. Suppl'ementary data and source code link are available at:
   http://www.isical.ac.in/bioinfo\_miu/ieee\_tcbb\_kemeny.rar.,}},
Publisher = {{IEEE COMPUTER SOC}},
Address = {{10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Sengupta, D (Reprint Author), Indian Stat Inst, Machine Intelligence Unit, Kolkata 700108, India.
   Sengupta, Debarka; Bandyopadhyay, Sanghamitra, Indian Stat Inst, Machine Intelligence Unit, Kolkata 700108, India.
   Pyne, Aroonalok; Maulik, Ujjwal, Jadavpur Univ, Comp Sci \& Engn Dept, Kolkata 700032, W Bengal, India.}},
DOI = {{10.1109/TCBB.2013.74}},
ISSN = {{1545-5963}},
EISSN = {{1557-9964}},
Keywords = {{Kemeny optimal aggregation; rank aggregation; microRNA; target
   prediction; simulated annealing; optimization}},
Keywords-Plus = {{MONTE-CARLO; PREDICTION}},
Research-Areas = {{Biochemistry \& Molecular Biology; Computer Science; Mathematics}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Computer Science, Interdisciplinary
   Applications; Mathematics, Interdisciplinary Applications; Statistics \&
   Probability}},
Author-Email = {{debarka\_r@isical.ac.in
   aroonalok.pyne@gmail.com
   umaulik@cse.jdvu.ac.in
   sanghami@isical.ac.in}},
Funding-Acknowledgement = {{Swamajayanti Fellowship scheme of the Department of Science and
   Technology, Government of India {[}DST/SJF/ET-02/2006-07]}},
Funding-Text = {{The authors would like to thank the financial support from the grant no.
   DST/SJF/ET-02/2006-07 under the Swamajayanti Fellowship scheme of the
   Department of Science and Technology, Government of India. The authors
   are also thankful to Prince Jain, an undergraduate student from the
   Department of Computer Science and Engineering, Jadavpur University, for
   participating in the implementation of the presented work.}},
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Number-of-Cited-References = {{26}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{IEEE-ACM Trans. Comput. Biol. Bioinform.}},
Doc-Delivery-Number = {{246PY}},
Unique-ID = {{ISI:000326552800017}},
}

@article{ ISI:000316748500003,
Author = {Clemencon, Stephan and Robbiano, Sylvain and Vayatis, Nicolas},
Title = {{Ranking data with ordinal labels: optimality and pairwise aggregation}},
Journal = {{MACHINE LEARNING}},
Year = {{2013}},
Volume = {{91}},
Number = {{1}},
Pages = {{67-104}},
Month = {{APR}},
Abstract = {{The paper describes key insights in order to grasp the nature of
   K-partite ranking. From the theoretical side, the various
   characterizations of optimal elements are fully described, as well as
   the likelihood ratio monotonicity condition on the underlying
   distribution which guarantees that such elements do exist. Then, a
   pairwise aggregation procedure based on Kendall tau is introduced to
   relate learning rules dedicated to bipartite ranking and solutions of
   the K-partite ranking problem. Criteria reflecting ranking performance
   under these conditions such as the ROC surface and its natural summary,
   the volume under the ROC surface (VUS), are then considered as targets
   for empirical optimization. The consistency of pairwise aggregation
   strategies are studied under these criteria and shown to be efficient
   under reasonable assumptions. Eventually, numerical results illustrate
   the relevance of the methodology proposed.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Robbiano, S (Reprint Author), Telecom ParisTech, LTCI, CNRS, UMR 5141, F-75634 Paris 13, France.
   Clemencon, Stephan; Robbiano, Sylvain, Telecom ParisTech, LTCI, CNRS, UMR 5141, F-75634 Paris 13, France.
   Vayatis, Nicolas, ENS Cachan, CMLA, CNRS, UMR 8536, F-94235 Cahan, France.
   Vayatis, Nicolas, UniverSud, F-94235 Cahan, France.}},
DOI = {{10.1007/s10994-012-5325-4}},
ISSN = {{0885-6125}},
EISSN = {{1573-0565}},
Keywords = {{K-partite ranking; Ordinal data; ROC surface; Volume under the ROC
   surface; Empirical risk minimization; Median ranking}},
Keywords-Plus = {{ROC ANALYSIS; GENERALIZATION BOUNDS; LINEAR ORDERS; CLASSIFICATION;
   MULTICLASS; CLASSIFIERS; CURVE; ALGORITHMS; BINARY; TASKS}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{stephan.clemencon@telecom-paristech.fr
   robbiano@telecom-paristech.fr}},
Cited-References = {{Audibert JY, 2007, ANN STAT, V35, P608, DOI 10.1214/009053606000001217.
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Number-of-Cited-References = {{60}},
Times-Cited = {{3}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{Mach. Learn.}},
Doc-Delivery-Number = {{114NN}},
Unique-ID = {{ISI:000316748500003}},
}

@article{ ISI:000314754000008,
Author = {Wang, Yang and Huang, Yalou and Pang, Xiaodong and Lu, Min and Xie,
   Maoqiang and Liu, Jie},
Title = {{Supervised rank aggregation based on query similarity for document
   retrieval}},
Journal = {{SOFT COMPUTING}},
Year = {{2013}},
Volume = {{17}},
Number = {{3}},
Pages = {{421-429}},
Month = {{MAR}},
Abstract = {{This paper is concerned with supervised rank aggregation, which aims to
   improve the ranking performance by combining the outputs from multiple
   rankers. However, there are two main shortcomings in previous rank
   aggregation approaches. First, the learned weights for base rankers do
   not distinguish the differences among queries. This is suboptimal since
   queries vary significantly in terms of ranking. Besides, most current
   aggregation functions do not directly optimize the evaluation measures
   in ranking. In this paper, the differences among queries are taken into
   consideration, and a supervised rank aggregation function is proposed.
   This aggregation function is directly optimizing the evaluation measure
   NDCG, referred to as RankAgg.NDCG, We prove that RankAgg.NDCG can
   achieve better NDCG performance than the linear combination of the base
   rankers. Experimental results performed on benchmark datasets show our
   approach outperforms a number of baseline approaches.}},
Publisher = {{SPRINGER}},
Address = {{233 SPRING ST, NEW YORK, NY 10013 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Wang, Y (Reprint Author), Nankai Univ, Coll Informat Technol Sci, 94 Weijin Rd, Tianjin 300071, Peoples R China.
   Wang, Yang; Huang, Yalou; Lu, Min; Liu, Jie, Nankai Univ, Coll Informat Technol Sci, Tianjin 300071, Peoples R China.
   Wang, Yang, Tianjin Elect Power Corp, Informat \& Commun Co, Tianjin 300010, Peoples R China.}},
DOI = {{10.1007/s00500-012-0917-2}},
ISSN = {{1432-7643}},
Keywords = {{Rank aggregation; Query similarity; Direct optimization of evaluation
   measures; Learning to rank; Document retrieval}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Computer Science,
   Interdisciplinary Applications}},
Author-Email = {{wangyang022@hotmail.com
   huangyl@nankai.edu.cn
   pangxd@mail.nankai.edu.cn
   lumin@mail.nankai.edu.cn
   xiemq@nankai.edu.cn
   nkjliu@nankai.edu.cn}},
Funding-Acknowledgement = {{High-Tech Research and Development (863) Program of China
   {[}2011AA05A117]; National Foundation of China {[}60673009]; Ministry of
   Education of China {[}65010571]; Microsoft Research Asia Foundation}},
Funding-Text = {{This work is supported by High-Tech Research and Development (863)
   Program of China under Grant No. 2011AA05A117, National Foundation of
   China under Grant No. 60673009, the Ministry of Education of China under
   Grant No. 65010571 and Microsoft Research Asia Foundation. We would like
   to thank Zhen Liao and Caihua Liu for their helpful discussions and
   suggestions.}},
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   Yue Y, 2007, P 30 ACM SIGIR C NET.}},
Number-of-Cited-References = {{22}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{8}},
Journal-ISO = {{Soft Comput.}},
Doc-Delivery-Number = {{087IE}},
Unique-ID = {{ISI:000314754000008}},
}

@article{ ISI:000313929600032,
Author = {Fields, Erica B. and Okudan, Guel E. and Ashour, Omar M.},
Title = {{Rank aggregation methods comparison: A case for triage prioritization}},
Journal = {{EXPERT SYSTEMS WITH APPLICATIONS}},
Year = {{2013}},
Volume = {{40}},
Number = {{4}},
Pages = {{1305-1311}},
Month = {{MAR}},
Abstract = {{This paper seeks to test and to determine a suitable aggregation method
   to represent a set of rankings made by individual decision makers (DMs).
   A case study for triage prioritization is used to test the aggregation
   methods. The triage is a decision-making process with which patients are
   prioritized according to their medical condition and chance of survival
   on arrival at the emergency department (ED). There is a lot of
   subjective decision-making in the process which leads to discrepancies
   among nurses. Four rank aggregation methods are applied to the
   prioritization data and then an expert evaluates the results and judges
   them on practicality and acceptability. The proposed recommendation for
   preference aggregation is the method of the estimation of utility
   intervals. Expert opinion is highly valued in a decision-making
   environment such as this, where experience and intuition are key to
   successful job performance and outcomes. (C) 2012 Elsevier Ltd. All
   rights reserved.}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Okudan, GE (Reprint Author), Penn State Univ, Sch Engn Design, 213T Hammond Bldg, University Pk, PA 16802 USA.
   Fields, Erica B.; Okudan, Guel E.; Ashour, Omar M., Penn State Univ, Harlod \& Inge Marcus Dept Ind \& Mfg Engn, University Pk, PA 16802 USA.
   Okudan, Guel E., Penn State Univ, Sch Engn Design, University Pk, PA 16802 USA.}},
DOI = {{10.1016/j.eswa.2012.08.060}},
ISSN = {{0957-4174}},
Keywords = {{Group decision making; Rank aggregation; Utility intervals; Mathematical
   programming models; Ordered weighted averaging (OWA); operator weights}},
Keywords-Plus = {{MULTICRITERIA DECISION-MAKING; OWA OPERATOR WEIGHTS; PREFERENCE
   STRUCTURES; DISTANCES; EMERGENCY}},
Research-Areas = {{Computer Science; Engineering; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Engineering, Electrical \&
   Electronic; Operations Research \& Management Science}},
Author-Email = {{ebf112@psu.edu
   gek3@engr.psu.edu
   oma110@psu.edu}},
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Number-of-Cited-References = {{28}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{6}},
Usage-Count-Since-2013 = {{23}},
Journal-ISO = {{Expert Syst. Appl.}},
Doc-Delivery-Number = {{076AT}},
Unique-ID = {{ISI:000313929600032}},
}

@article{ ISI:000314445400009,
Author = {Bruno, Giulia and Fiori, Alessandro},
Title = {{MicroClAn: Microarray clustering analysis}},
Journal = {{JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING}},
Year = {{2013}},
Volume = {{73}},
Number = {{3}},
Pages = {{360-370}},
Month = {{MAR}},
Abstract = {{Evaluating clustering results is a fundamental task in microarray data
   analysis, due to the lack of enough biological knowledge to know in
   advance the true partition of genes. Many quality indexes for gene
   clustering evaluation have been proposed. A critical issue in this
   domain is to compare and aggregate quality indexes to select the best
   clustering algorithm and the optimal parameter setting for a dataset.
   Furthermore, due to the huge amount of data generated by microarray
   experiments and the requirement of external resources such as ontologies
   to compute biological indexes, another critical issue is the performance
   decline in term of execution time. Thus, the distributed computation of
   algorithms and quality indexes becomes essential. Addressing these
   issues, this paper presents the MicroClAn framework, a distributed
   system to evaluate and compare clustering algorithms using the most
   exploited quality indexes. The best solution is selected through a
   two-step ranking aggregation of the ranks produced by quality indexes. A
   new index oriented to the biological validation of microarray clustering
   results is also introduced. Several scheduling strategies integrated in
   the framework allow to distribute tasks in the grid environment to
   optimize the completion time. Experimental results show the
   effectiveness of our aggregation strategy in identifying the best rank
   among different clustering algorithms. Moreover, our framework achieves
   good performance in terms of completion time with few computational
   resources. (c) 2012 Elsevier Inc. All rights reserved.}},
Publisher = {{ACADEMIC PRESS INC ELSEVIER SCIENCE}},
Address = {{525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Fiori, A (Reprint Author), FPRC, Inst Canc Res \& Treatment IRCC, Str Prov 142,Km 3-95, I-10060 Candiolo, Italy.
   Bruno, Giulia, Politecn Torino, Dipartimento Ingn Gest \& Prod, I-10129 Turin, Italy.
   Fiori, Alessandro, FPRC, Inst Canc Res \& Treatment IRCC, I-10060 Candiolo, Italy.}},
DOI = {{10.1016/j.jpdc.2012.09.008}},
ISSN = {{0743-7315}},
Keywords = {{Microarray; Clustering analysis; Quality indexes; Rank aggregation;
   Scheduling strategies}},
Keywords-Plus = {{GENE-EXPRESSION DATA; WEIGHTED RANK AGGREGATION; VALIDATION; ALGORITHMS;
   CLASSIFICATION}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Theory \& Methods}},
Author-Email = {{giulia.bruno@polito.it
   alessandro.fiori@ircc.it}},
ORCID-Numbers = {{Bruno, Giulia/0000-0001-5585-647X}},
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Number-of-Cited-References = {{51}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{8}},
Journal-ISO = {{J. Parallel Distrib. Comput.}},
Doc-Delivery-Number = {{083EL}},
Unique-ID = {{ISI:000314445400009}},
}

@article{ ISI:000314538100024,
Author = {Ghahfarokhi, Behrouz Shahgholi and Movahhedinia, Naser},
Title = {{Context-Aware Handover Decision in an Enhanced Media Independent
   Handover Framework}},
Journal = {{WIRELESS PERSONAL COMMUNICATIONS}},
Year = {{2013}},
Volume = {{68}},
Number = {{4}},
Pages = {{1633-1671}},
Month = {{FEB}},
Abstract = {{Recent developments in heterogeneous mobile networks emphasize the
   necessity of more intelligent and context-aware handover decisions.
   However, the complexity and overhead of collecting and managing context
   information are the main difficulties in context-aware handovers. Media
   independent handover (MIH) framework which has been proposed by IEEE
   802.21 only provides static context of access networks through its
   information service. This paper elaborates the idea of handoff-aware
   network context gathering for renewal of dynamic context in MIH
   information server. An extension is proposed on MIH framework to
   efficiently accommodate the dynamic context of access networks along
   with the ordinary static context in IS. The paper presents analytical
   evaluation of the proposed context gathering method in terms of context
   access latency and signalling overhead. Also, the paper presents a
   policy-based context-aware handover model based on the proposed
   extension. A well defined policy format is proposed for straight
   description of users', devices', and applications' preferences and
   requirements. In contrast to traditional policy-based methods, a
   multi-policy scheme is proposed that exploits rank aggregation methods
   to employ a set of matching policies in target point of attachment
   selection. Simulations have been carried out in NS2 to verify the
   performance of the proposed context gathering method and the proposed
   handover decision model. Simulation results show better performance in
   terms of evaluation metrics.}},
Publisher = {{SPRINGER}},
Address = {{233 SPRING ST, NEW YORK, NY 10013 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ghahfarokhi, BS (Reprint Author), Univ Isfahan, Dept Informat Technol Engn, Esfahan, Iran.
   Ghahfarokhi, Behrouz Shahgholi, Univ Isfahan, Dept Informat Technol Engn, Esfahan, Iran.
   Movahhedinia, Naser, Univ Isfahan, Dept Comp Engn, Esfahan, Iran.
   Movahhedinia, Naser, Univ Isfahan, Dept Comp, Esfahan, Iran.}},
DOI = {{10.1007/s11277-012-0543-4}},
ISSN = {{0929-6212}},
EISSN = {{1572-834X}},
Keywords = {{Context awareness; Media independent handover; Handoff aware network
   context gathering; Policy based networking; Rank aggregation}},
Keywords-Plus = {{HETEROGENEOUS WIRELESS NETWORKS; MANAGEMENT; IEEE-802.21; MULTIMEDIA;
   SERVICES; QUALITY}},
Research-Areas = {{Telecommunications}},
Web-of-Science-Categories  = {{Telecommunications}},
Author-Email = {{shahgholi@eng.ui.ac.ir
   naserm@eng.ui.ac.ir}},
Cited-References = {{Ahmed T., 2006, P 11 IEEE S COMP COM, P795.
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Number-of-Cited-References = {{46}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{9}},
Journal-ISO = {{Wirel. Pers. Commun.}},
Doc-Delivery-Number = {{084KN}},
Unique-ID = {{ISI:000314538100024}},
}

@article{ ISI:000314297800002,
Author = {Zhao, Xiaojian and Yuan, Jin and Wang, Meng and Li, Guangda and Hong,
   Richang and Li, Zhoujun and Chua, Tat-Seng},
Title = {{Video recommendation over multiple information sources}},
Journal = {{MULTIMEDIA SYSTEMS}},
Year = {{2013}},
Volume = {{19}},
Number = {{1, SI}},
Pages = {{3-15}},
Month = {{FEB}},
Abstract = {{Video recommendation is an important tool to help people access
   interesting videos. In this paper, we propose a universal scheme to
   integrate rich information for personalized video recommendation. Our
   approach regards video recommendation as a ranking task. First, it
   generates multiple ranking lists by exploring different information
   sources. In particular, one novel source user's relationship strength is
   inferred through the online social network and applied to recommend
   videos. Second, based on multiple ranking lists, a multi-task rank
   aggregation approach is proposed to integrate these ranking lists to
   generate a final result for video recommendation. It is shown that our
   scheme is flexible that can easily incorporate other methods by adding
   their generated ranking lists into our multi-task rank aggregation
   approach. We conduct experiments on a large dataset with 76 users and
   more than 11,000 videos. The experimental results demonstrate the
   feasibility and effectiveness of our approach.}},
Publisher = {{SPRINGER}},
Address = {{233 SPRING ST, NEW YORK, NY 10013 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Wang, M (Reprint Author), Hefei Univ Technol, Sch Comp \& Informat, Hefei 230009, Peoples R China.
   Zhao, Xiaojian; Li, Guangda, Beihang Univ, State Key Lab Software Dev Environm, Beijing 100191, Peoples R China.
   Yuan, Jin; Li, Guangda; Chua, Tat-Seng, Natl Univ Singapore, Sch Comp, Singapore 117590, Singapore.
   Wang, Meng; Hong, Richang, Hefei Univ Technol, Sch Comp \& Informat, Hefei 230009, Peoples R China.}},
DOI = {{10.1007/s00530-012-0267-z}},
ISSN = {{0942-4962}},
EISSN = {{1432-1882}},
Keywords = {{Video recommendation; Rich information; Online social network;
   Multi-task rank aggregation}},
Keywords-Plus = {{SYSTEMS; SIMILARITY; DISTANCE; RANKING; SEARCH}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Computer Science, Theory \&
   Methods}},
Author-Email = {{zhaoxj01@gmail.com
   yuanjin@comp.nus.edu.sg
   eric.mengwang@gmail.com
   guangda10@gmail.com
   hongrc.hfut@gmail.com
   lizj@buaa.edu.cn
   chuats@comp.nus.edu.sg}},
Funding-Acknowledgement = {{Beihang University {[}YWF-12-RBYJ-012]; National Natural Science
   Foundation of China {[}61170189, 60973105]; State Key Laboratory of
   Software Development Environment {[}SKLSDE-2011ZX-03]; Singapore
   National Research Foundation \& Interactive Digital Media R\&D Program
   Office, MDA {[}WBS:R-252-300-001-490]}},
Funding-Text = {{This work was supported by the Innovation Scholarship for Ph.D. students
   at Beihang University under research grant (YWF-12-RBYJ-012), the
   National Natural Science Foundation of China (61170189, 60973105), the
   Fund of the State Key Laboratory of Software Development Environment
   under Grant No. SKLSDE-2011ZX-03 and the Singapore National Research
   Foundation \& Interactive Digital Media R\&D Program Office, MDA under
   research grant (WBS:R-252-300-001-490). The authors would like to thank
   the editors and the anonymous reviewers for their valuable comments and
   remarks on this paper.}},
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Number-of-Cited-References = {{47}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{16}},
Journal-ISO = {{Multimedia Syst.}},
Doc-Delivery-Number = {{081DU}},
Unique-ID = {{ISI:000314297800002}},
}

@article{ ISI:000325801300016,
Author = {Charrois, Theresa L. and Appleton, Michelle},
Title = {{Online Debates to Enhance Critical Thinking in Pharmacotherapy}},
Journal = {{AMERICAN JOURNAL OF PHARMACEUTICAL EDUCATION}},
Year = {{2013}},
Volume = {{77}},
Number = {{8}},
Abstract = {{Objectives. To assess the impact of teaching strategies on the
   complexity and structure of students' arguments and type of informal
   reasoning used in arguments.
   Design. Students were given an introduction to argumentation followed by
   2 formal debates, with feedback provided in between.
   Assessment. Four debate groups were randomly selected for evaluation. In
   debate 1, all groups posted 1 argument, and all 4 arguments were
   rationalistic and ranked as high-level arguments. In debate 2, members
   of the 4 groups posted a total of 33 arguments, which were evaluated and
   received an overall median ranking lower than that for debate 1. All
   debates were categorized as rationalistic.
   Conclusion. Students were able to formulate rationalistic arguments to
   therapeutic controversies; however, their level of argumentation
   decreased over the course of the study. Changes planned for the future
   include conducting the debates in the context of patient scenarios to
   increase practical applicability.}},
Publisher = {{AMER ASSOC COLL PHARMACY}},
Address = {{1426 PRINCE STREET, ALEXANDRIA, VA 22314-2815 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Charrois, TL (Reprint Author), Curtin Univ, Sch Pharm, GPO Box U1987, Perth, WA 6845, Australia.
   Charrois, Theresa L.; Appleton, Michelle, Curtin Univ, Sch Pharm, Curtin Hlth Innovat Res Inst, Perth, WA 6845, Australia.}},
Article-Number = {{170}},
ISSN = {{0002-9459}},
EISSN = {{1553-6467}},
Keywords = {{debate; online; pharmacotherapy; critical thinking}},
Keywords-Plus = {{STUDENTS; SKILLS; EDUCATION; SCIENCE; IMPACT}},
Research-Areas = {{Education \& Educational Research; Pharmacology \& Pharmacy}},
Web-of-Science-Categories  = {{Education, Scientific Disciplines; Pharmacology \& Pharmacy}},
Author-Email = {{t.charrois@curtin.edu.au}},
Cited-References = {{Accreditation Council on Pharmacy Education, 2011, ACCREDITATION STANDA.
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Number-of-Cited-References = {{15}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Am. J. Pharm. Educ.}},
Doc-Delivery-Number = {{236MM}},
Unique-ID = {{ISI:000325801300016}},
}

@article{ ISI:000314530200002,
Author = {Clemencon, Stephan and Depecker, Marine and Vayatis, Nicolas},
Title = {{Ranking Forests}},
Journal = {{JOURNAL OF MACHINE LEARNING RESEARCH}},
Year = {{2013}},
Volume = {{14}},
Pages = {{39-73}},
Month = {{JAN}},
Abstract = {{The present paper examines how the aggregation and feature randomization
   principles underlying the algorithm RANDOM FOREST (Breiman, 2001) can be
   adapted to bipartite ranking. The approach taken here is based on
   nonparametric scoring and ROC curve optimization in the sense of the AUC
   criterion. In this problem, aggregation is used to increase the
   performance of scoring rules produced by ranking trees, as those
   developed in Clemencon and Vayatis (2009c). The present work describes
   the principles for building median scoring rules based on concepts from
   rank aggregation. Consistency results are derived for these aggregated
   scoring rules and an algorithm called RANKING FOREST is presented.
   Furthermore, various strategies for feature randomization are explored
   through a series of numerical experiments on artificial data sets.}},
Publisher = {{MICROTOME PUBL}},
Address = {{31 GIBBS ST, BROOKLINE, MA 02446 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Clemencon, S (Reprint Author), Telecom ParisTech, Inst Telecom LTCI, UMR Telecom ParisTech CNRS 5141, 46 Rue Barrault, F-75634 Paris, France.
   Clemencon, Stephan; Depecker, Marine, Telecom ParisTech, Inst Telecom LTCI, UMR Telecom ParisTech CNRS 5141, F-75634 Paris, France.
   Vayatis, Nicolas, ENS Cachan, CMLA, UMR ENS Cachan CNRS 8536, F-94230 Cachan, France.}},
ISSN = {{1532-4435}},
Keywords = {{bipartite ranking; nonparametric scoring; classification data; ROC
   optimization; AUC criterion; tree-based ranking rules; bootstrap;
   bagging; rank aggregation; median ranking; feature randomization}},
Keywords-Plus = {{AGGREGATION; PREFERENCES}},
Research-Areas = {{Automation \& Control Systems; Computer Science}},
Web-of-Science-Categories  = {{Automation \& Control Systems; Computer Science, Artificial Intelligence}},
Author-Email = {{STEPHAN.CLEMENCON@TELECOM-PARISTECH.FR
   MARINE-DEPECKER@TELECOM-PARISTECH.FR
   NICOLAS.VAYATIS@CMLA.ENS-CACHAN.FR}},
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Number-of-Cited-References = {{54}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{J. Mach. Learn. Res.}},
Doc-Delivery-Number = {{084HU}},
Unique-ID = {{ISI:000314530200002}},
}

@article{ ISI:000313029700012,
Author = {Monwar, Md Maruf and Gavrilova, Marina},
Title = {{Markov chain model for multimodal biometric rank fusion}},
Journal = {{SIGNAL IMAGE AND VIDEO PROCESSING}},
Year = {{2013}},
Volume = {{7}},
Number = {{1}},
Pages = {{137-149}},
Month = {{JAN}},
Abstract = {{Multimodal biometric aims at increasing reliability of biometric systems
   through utilizing more than one biometric in decision-making process. An
   effective fusion scheme is necessary for combining information from
   various sources. Such information can be integrated at several distinct
   levels, such as sensor level, feature level, match score level, rank
   level, and decision level. In this paper, we present a multimodal
   biometric system utilizing face, iris, and ear biometric features
   through rank level fusion method using novel Markov chain approach. We
   first apply fisherimage technique to face and ear image databases for
   recognition and Hough transform and Hamming distance techniques for iris
   image recognition. The main contribution is in introducing Markov chain
   approach for biometric rank aggregation. One of the distinctive features
   of this method is that it satisfies the Condorcet criterion, which is
   essential in any fair rank aggregation system. The experimentation shows
   superiority of the proposed approach to other recently introduced
   biometric rank aggregation methods. The developed system can be
   effectively used by security and intelligence services for controlling
   access to prohibited areas and protecting important national or public
   information.}},
Publisher = {{SPRINGER LONDON LTD}},
Address = {{236 GRAYS INN RD, 6TH FLOOR, LONDON WC1X 8HL, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Monwar, MM (Reprint Author), Univ Calgary, Dept Comp Sci, 2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada.
   Monwar, Md Maruf; Gavrilova, Marina, Univ Calgary, Dept Comp Sci, Calgary, AB T2N 1N4, Canada.}},
DOI = {{10.1007/s11760-011-0226-8}},
ISSN = {{1863-1703}},
Keywords = {{Pattern recognition; Multimodal biometric system; Rank level fusion;
   Markov chain}},
Keywords-Plus = {{IRIS RECOGNITION; FACE-RECOGNITION; IDENTIFICATION; VERIFICATION;
   SYSTEMS; LEVEL}},
Research-Areas = {{Engineering; Imaging Science \& Photographic Technology}},
Web-of-Science-Categories  = {{Engineering, Electrical \& Electronic; Imaging Science \& Photographic
   Technology}},
Author-Email = {{mmmonwar@cpsc.ucalgary.ca
   marina@cpsc.ucalgary.ca}},
Cited-References = {{Agresti A., 2007, INTRO CATEGORICAL DA.
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Number-of-Cited-References = {{39}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{9}},
Journal-ISO = {{Signal Image Video Process.}},
Doc-Delivery-Number = {{063VI}},
Unique-ID = {{ISI:000313029700012}},
}

@article{ ISI:000313618800011,
Author = {Zhang, Yida and Baker, Susan S. and Baker, Robert D. and Zhu, Ruixin and
   Zhu, Lixin},
Title = {{Systematic Analysis of the Gene Expression in the Livers of Nonalcoholic
   Steatohepatitis: Implications on Potential Biomarkers and Molecular
   Pathological Mechanism}},
Journal = {{PLOS ONE}},
Year = {{2012}},
Volume = {{7}},
Number = {{12}},
Month = {{DEC 26}},
Abstract = {{Non-alcoholic steatohepatitis (NASH) is a severe form of non-alcoholic
   fatty liver disease (NAFLD). The molecular pathological mechanism of
   NASH is poorly understood. Recently, high throughput data such as
   microarray data together with bioinformatics methods have become a
   powerful way to identify biomarkers and to investigate pathogenesis of
   diseases. Taking advantage of well characterized microarray datasets of
   NASH livers, we performed a systematic analysis of potential biomarkers
   and possible pathological mechanism of NASH from a bioinformatics
   perspective. CodeLink Human Whole Genome Bioarrays were analyzed to find
   differentially expressed genes (DEGs) between controls and NASH
   patients. Four methods were used to identify DEGs and the intersection
   of DEGs identified by these methods was subsequently used for both
   biomarker prediction and molecular pathological mechanism analysis. For
   biomarker prediction, rank aggregation was used to rank DEGs identified
   by all these methods according to their significance of different
   expression. Alcohol dehydrogenase 4 (ADH4) exhibited the highest rank
   suggesting the most significant differential expression between normal
   and disease condition. Together with the previous report demonstrating
   the association between ADH4 and the pathogenesis of NASH, our data
   suggest that ADH4 could be a potential biomarker for NASH. For molecular
   pathological mechanism analysis, two clusters of highly correlated
   annotation terms and genes in these terms were identified based on the
   intersection of DEGs. Then, pathways enriched with these genes were
   identified to construct the network. Using this network, both for the
   first time, amino acid catabolism is implicated to play a pivotal role
   and urea cycle is implicated to be involved in the development of NASH.
   The results of our study identified potential biomarkers and suggested
   possible molecular pathological mechanism of NASH. These findings
   provide a comprehensive and systematic understanding of the pathogenesis
   of NASH and may facilitate the diagnosis, prevention and treatment of
   NASH.}},
Publisher = {{PUBLIC LIBRARY SCIENCE}},
Address = {{1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Zhu, RX (Reprint Author), Tongji Univ, Dept Bioinformat, Shanghai 200092, Peoples R China.
   Zhang, Yida; Zhu, Ruixin, Tongji Univ, Dept Bioinformat, Shanghai 200092, Peoples R China.
   Baker, Susan S.; Baker, Robert D.; Zhu, Lixin, SUNY Buffalo, Digest Dis \& Nutr Ctr, Dept Pediat, Buffalo, NY 14260 USA.}},
DOI = {{10.1371/journal.pone.0051131}},
Article-Number = {{e51131}},
ISSN = {{1932-6203}},
Keywords-Plus = {{WEIGHTED RANK AGGREGATION; ALCOHOL-DEHYDROGENASE; MICROARRAY DATA;
   MITOCHONDRIAL ABNORMALITIES; INSULIN-RESISTANCE; ETHANOL-PRODUCTION;
   ACID METABOLISM; FOLLOW-UP; DISEASE; KEGG}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{rxzhu@tongji.edu.cn
   lixinzhu@buffalo.edu}},
Funding-Acknowledgement = {{Peter and Tommy Fund, Inc., Buffalo, NY; National Natural Science
   Foundation of China {[}31200986, 30976611]; Research Fund for the
   Doctoral Program of Higher Education of China {[}20100072120050]}},
Funding-Text = {{This work was supported by an unrestricted grant from the Peter and
   Tommy Fund, Inc., Buffalo, NY, http://thepeterandtommyfund.org (to SSB),
   a departmental start-up fund (to LZ), National Natural Science
   Foundation of China 31200986, 30976611(to RZ), and Research Fund for the
   Doctoral Program of Higher Education of China 20100072120050 (to RZ).
   The funders had no role in study design, data collection and analysis,
   decision to publish, or preparation of the manuscript.}},
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Number-of-Cited-References = {{70}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{11}},
Journal-ISO = {{PLoS One}},
Doc-Delivery-Number = {{071TV}},
Unique-ID = {{ISI:000313618800011}},
}

@article{ ISI:000314689000001,
Author = {Wu, Shicheng and Xu, Yawen and Feng, Zeny and Yang, Xiaojian and Wang,
   Xiaogang and Gao, Xin},
Title = {{Multiple-platform data integration method with application to combined
   analysis of microarray and proteomic data}},
Journal = {{BMC BIOINFORMATICS}},
Year = {{2012}},
Volume = {{13}},
Month = {{DEC 2}},
Abstract = {{Background: It is desirable in genomic studies to select biomarkers that
   differentiate between normal and diseased populations based on related
   data sets from different platforms, including microarray expression and
   proteomic data. Most recently developed integration methods focus on
   correlation analyses between gene and protein expression profiles. The
   correlation methods select biomarkers with concordant behavior across
   two platforms but do not directly select differentially expressed
   biomarkers. Other integration methods have been proposed to combine
   statistical evidence in terms of ranks and p-values, but they do not
   account for the dependency relationships among the data across
   platforms.
   Results: In this paper, we propose an integration method to perform
   hypothesis testing and biomarkers selection based on multi-platform data
   sets observed from normal and diseased populations. The types of test
   statistics can vary across the platforms and their marginal
   distributions can be different. The observed test statistics are
   aggregated across different data platforms in a weighted scheme, where
   the weights take into account different variabilities possessed by test
   statistics. The overall decision is based on the empirical distribution
   of the aggregated statistic obtained through random permutations.
   Conclusion: In both simulation studies and real biological data
   analyses, our proposed method of multi-platform integration has better
   control over false discovery rates and higher positive selection rates
   than the uncombined method. The proposed method is also shown to be more
   powerful than rank aggregation method.}},
Publisher = {{BIOMED CENTRAL LTD}},
Address = {{236 GRAYS INN RD, FLOOR 6, LONDON WC1X 8HL, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Gao, X (Reprint Author), York Univ, Dept Math \& Stat, 4700 Keele, Toronto, ON M3J 1P3, Canada.
   Wu, Shicheng; Xu, Yawen; Wang, Xiaogang; Gao, Xin, York Univ, Dept Math \& Stat, Toronto, ON M3J 1P3, Canada.
   Feng, Zeny; Yang, Xiaojian, Univ Guelph, Dept Math \& Stat, Guelph, ON N1G 2W1, Canada.}},
DOI = {{10.1186/1471-2105-13-320}},
Article-Number = {{320}},
ISSN = {{1471-2105}},
Keywords-Plus = {{GENOMIC DATA FUSION; STREPTOMYCES-COELICOLOR; GENE-EXPRESSION;
   METAANALYSIS; FRAMEWORK}},
Research-Areas = {{Biochemistry \& Molecular Biology; Biotechnology \& Applied
   Microbiology; Mathematical \& Computational Biology}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Biotechnology \& Applied Microbiology;
   Mathematical \& Computational Biology}},
Author-Email = {{xingao@mathstat.yorku.ca}},
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   Jayapal KP, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0002097.
   Nieselt K, 2010, BMC GENOMICS, V11, DOI 10.1186/1471-2164-11-10.}},
Number-of-Cited-References = {{21}},
Times-Cited = {{3}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{8}},
Journal-ISO = {{BMC Bioinformatics}},
Doc-Delivery-Number = {{086MR}},
Unique-ID = {{ISI:000314689000001}},
}

@article{ ISI:000305727400002,
Author = {Guimaraes Pedronette, Daniel Carlos and Torres, Ricardo da S.},
Title = {{Exploiting pairwise recommendation and clustering strategies for image
   re-ranking}},
Journal = {{INFORMATION SCIENCES}},
Year = {{2012}},
Volume = {{207}},
Pages = {{19-34}},
Month = {{NOV 10}},
Abstract = {{In Content-based Image Retrieval (CBIR) systems, accurately ranking
   collection images is of great relevance. Users are interested in the
   returned images placed at the first positions, which usually are the
   most relevant ones. Commonly, image content descriptors are used to
   compute ranked lists in CBIR systems. In general, these systems perform
   only pairwise image analysis, that is, compute similarity measures
   considering only pairs of images, ignoring the rich information encoded
   in the relations among several images. This paper presents a novel
   re-ranking approach used to improve the effectiveness of CBIR tasks by
   exploring relations among images. In our approach, a
   recommendation-based strategy is combined with a clustering method. Both
   exploit contextual information encoded in ranked lists computed by CBIR
   systems. We conduct several experiments to evaluate the proposed method.
   Our experiments consider shape, color, and texture descriptors and
   comparisons with other post-processing methods. Experimental results
   demonstrate the effectiveness of our method. (C) 2012 Elsevier Inc. All
   rights reserved.}},
Publisher = {{ELSEVIER SCIENCE INC}},
Address = {{360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Pedronette, DCG (Reprint Author), Univ Estadual Campinas, RECOD Lab, IC, UNICAMP, Campinas, SP, Brazil.
   Guimaraes Pedronette, Daniel Carlos; Torres, Ricardo da S., Univ Estadual Campinas, RECOD Lab, IC, UNICAMP, Campinas, SP, Brazil.}},
DOI = {{10.1016/j.ins.2012.04.032}},
ISSN = {{0020-0255}},
Keywords = {{Content-based image retrieval; Re-ranking; Rank aggregation;
   Recommendation}},
Keywords-Plus = {{RETRIEVAL; CLASSIFICATION; DESCRIPTORS; RECOGNITION; DISTANCE; CONTOUR;
   LISTS}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems}},
Author-Email = {{dcarlos@ic.unicamp.br
   rtorres@ic.unicamp.br}},
ResearcherID-Numbers = {{Pedronette, Daniel/E-7817-2015}},
Funding-Acknowledgement = {{AMD; CAPES; FAPESP {[}2007/52015-0, 2009/18438-7]; FAEPEX; CNPq;
   DGA/UNICAMP}},
Funding-Text = {{Authors thank AMD, CAPES, FAPESP (grants 2007/52015-0 and 2009/18438-7),
   FAEPEX, and CNPq for financial support. Authors also thank DGA/UNICAMP
   for its support in this work.}},
Cited-References = {{Ciocca G, 2011, INFORM SCIENCES, V181, P4943, DOI 10.1016/j.ins.2011.06.025.
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Number-of-Cited-References = {{44}},
Times-Cited = {{10}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{8}},
Journal-ISO = {{Inf. Sci.}},
Doc-Delivery-Number = {{964WM}},
Unique-ID = {{ISI:000305727400002}},
}

@article{ ISI:000307526200005,
Author = {Rybinski, Mikolaj and Gambin, Anna},
Title = {{Model-based selection of the robust JAK-STAT activation mechanism}},
Journal = {{JOURNAL OF THEORETICAL BIOLOGY}},
Year = {{2012}},
Volume = {{309}},
Pages = {{34-46}},
Month = {{SEP 21}},
Abstract = {{JAM-STAT pathway family is a principal signaling mechanism in eukaryotic
   cells. Evolutionary conserved roles of this mechanism include control
   over fundamental processes such as cell growth or apoptosis.
   Deregulation of the JAM-STAT signaling is frequently associated with
   cancerogenesis. JAK-STAT pathways become hyper-activated in many human
   tumors. Therefore, components of these pathways are an attractive target
   for drugs, which design requires as adequate models as possible.
   Although, in principle, JAK-STAT signaling is relatively simple, the
   ambiguities in a receptor activation prevent a clear explanation of the
   underlying molecular mechanism.
   Here, we compare four variants of a computational model of the
   JAK1/2-STAT1 signaling pathway. These variants capture known, basic
   discrepancies in the mechanism of activation of a cytokine receptor, in
   the context of all key components of the pathway. We carry out a
   comparative analysis using mass action kinetics. The investigated
   differences are so marginal that all models satisfy a goodness of fit
   criteria to the extent that the state of the art Bayesian model
   selection (BMS) method fails to significantly promote one model.
   Therefore, we comparatively investigate changes in a robustness of the
   JAK1/2-STAT1 pathway variants using the global sensitivity analysis
   method (GSA), complemented with the identifiability analysis (IA). Both
   BMS and GSA are used to analyze the models for the varying parameter
   values. We found out that, both BMS and GSA, narrowed down to the
   receptor activation component, slightly promote the least complex model.
   Further, insightful, comprehensive GSA, motivated by the concept of
   robustness, allowed us to show that the precise order of reactions of a
   ligand binding and a receptor dimerization is not as important as the
   on-membrane pre-assembly of the dimers in the absence of ligand.
   The main value of this work is an evaluation of the usefulness of
   different model selection methods in a frequently encountered, but not
   much discussed case of a model of a considerable size, which has several
   variants differing at peripheries. In such situation, all considered
   variants can reach nearly perfect agreement with respect to their
   numerical simulations results and, most often, the sufficient
   experimental data to test against is not available. We argue that in
   such an adverse setting, the GSA and IA, although not directly
   corresponding to the model selection problem, can be more informative
   than the representative, generalizability-based approaches to this task.
   An additional insight into how the responsibility for the network
   dynamics spreads among model parameters, enables more conscious,
   expert-mediated choice of the preferred model. (C) 2012 Elsevier Ltd.
   All rights reserved.}},
Publisher = {{ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD}},
Address = {{24-28 OVAL RD, LONDON NW1 7DX, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Rybinski, M (Reprint Author), Univ Warsaw, Inst Informat, Ul Banacha 2, Warsaw, Poland.
   Rybinski, Mikolaj; Gambin, Anna, Univ Warsaw, Inst Informat, Warsaw, Poland.
   Rybinski, Mikolaj; Gambin, Anna, Polish Acad Sci, Mossakowski Med Res Ctr, Warsaw, Poland.}},
DOI = {{10.1016/j.jtbi.2012.04.031}},
ISSN = {{0022-5193}},
EISSN = {{1095-8541}},
Keywords = {{Signaling pathway; Model selection; Sensitivity analysis; Robustness;
   Identifiability analysis}},
Keywords-Plus = {{SIGNAL-TRANSDUCTION PATHWAY; WEIGHTED RANK AGGREGATION; GAMMA RECEPTOR
   COMPLEX; MARKUP LANGUAGE SBML; SYSTEMS BIOLOGY; SENSITIVITY-ANALYSIS;
   BIOCHEMICAL PATHWAYS; PARAMETER-ESTIMATION; MATHEMATICAL-MODELS;
   EXPERIMENTAL-DESIGN}},
Research-Areas = {{Life Sciences \& Biomedicine - Other Topics; Mathematical \&
   Computational Biology}},
Web-of-Science-Categories  = {{Biology; Mathematical \& Computational Biology}},
Author-Email = {{trybik@mimuw.edu.pl
   aniag@mimuw.edu.pl}},
ResearcherID-Numbers = {{Gambin, Anna/I-3580-2012
   Rybinski, Mikolaj/B-7135-2013}},
ORCID-Numbers = {{Gambin, Anna/0000-0003-3476-3017
   Rybinski, Mikolaj/0000-0003-1397-6291}},
Funding-Acknowledgement = {{Polish Ministry of Science and Higher Education {[}N N206 356036];
   Biocentrum Ochota Project {[}POIG.02.03.00-00-003/09]; European Social
   Fund}},
Funding-Text = {{These studies were partially supported by Polish Ministry of Science and
   Higher Education Grant N N206 356036 and by the Biocentrum Ochota
   Project (POIG.02.03.00-00-003/09). The first author is a scholar within
   the Human Capital Operational Programme financed by European Social Fund
   and state budget. This paper was written for the benefit of University
   of Zielona Gora.}},
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Number-of-Cited-References = {{62}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{14}},
Journal-ISO = {{J. Theor. Biol.}},
Doc-Delivery-Number = {{988YA}},
Unique-ID = {{ISI:000307526200005}},
}

@article{ ISI:000307215200019,
Author = {Simko, Ivan and Hayes, Ryan J. and Kramer, Matthew},
Title = {{Computing Integrated Ratings from Heterogeneous Phenotypic Assessments:
   A Case Study of Lettuce Postharvest Quality and Downy Mildew Resistance}},
Journal = {{CROP SCIENCE}},
Year = {{2012}},
Volume = {{52}},
Number = {{5}},
Pages = {{2131-2142}},
Month = {{SEP}},
Abstract = {{Comparing performance of a large number of accessions simultaneously is
   not always possible. Frequently, only subsets of all accessions are
   tested in separate trials with only some (or none) of the accessions
   overlapping between subsets. Using standard statistical approaches to
   combine data from such a sparsely populated accession x trial matrix is
   precluded if different rating scales are used to evaluate accessions in
   those trials. Here we compare two approaches that can compute an overall
   linear rating for the performance of all accessions across a set of
   trials, even for accessions that were never tested together and were
   rated on dissimilar scales. We use data from lettuce (Lactuca sativa L.)
   postharvest quality collected on 178 accessions in 18 trials and
   assessment of lettuce resistance to downy mildew (Bremia lactucae Regel)
   performed on 583 accessions in 53 trials. The projected values (PV)
   approach uses a combination of principal component analysis and
   resampling to merge trial results and calculates an overall rating from
   real values. In contrast, the rank-aggregation (RA) approach uses an
   extension of the Rasch model to combine rank-ordered data from
   individual trials. We found high correlation between ratings produced by
   the two approaches for the postharvest quality (r = 0.803) and the
   resistance to downy mildew (r = 0.748). Combining data from multiple
   experiments identified lettuce accessions with a high level of
   resistance to the disease and a slow rate of deterioration when
   processed for salad. The PV and RA approaches also allow combining data
   from different laboratories or databases.}},
Publisher = {{CROP SCIENCE SOC AMER}},
Address = {{677 S SEGOE ROAD, MADISON, WI 53711 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Simko, I (Reprint Author), ARS, USDA, US Agr Res Stn, 1636 E Alisal St, Salinas, CA 93905 USA.
   Simko, Ivan; Hayes, Ryan J., ARS, USDA, US Agr Res Stn, Salinas, CA 93905 USA.
   Kramer, Matthew, ARS, USDA, Biometr Consulting Serv, Henry A Wallace Agr Res Ctr, Beltsville, MD 20705 USA.}},
DOI = {{10.2135/cropsci2012.02.0111}},
ISSN = {{0011-183X}},
Keywords-Plus = {{BREMIA-LACTUCAE REGEL; FIELD-RESISTANCE; ROMAINE LETTUCE; GRAND-RAPIDS;
   SHELF-LIFE; INHERITANCE; MICROARRAY; ICEBERG; MODEL}},
Research-Areas = {{Agriculture}},
Web-of-Science-Categories  = {{Agronomy}},
Author-Email = {{ivan.simko@ars.usda.gov}},
ResearcherID-Numbers = {{Simko, Ivan/J-6048-2012}},
ORCID-Numbers = {{Simko, Ivan/0000-0002-8769-8477}},
Funding-Acknowledgement = {{California Leafy Greens Research Program; Arizona Department of
   Agriculture, Agricultural Consultation and Training}},
Funding-Text = {{The authors thank Amy Atallah and Jose Orozco for assistance with
   evaluations of the trials. The California Leafy Greens Research Program
   and the Arizona Department of Agriculture, Agricultural Consultation and
   Training, have funded a portion of this project. The views and findings
   presented are the Grantee's and do not necessarily represent those of
   the State or the Arizona Department of Agriculture. Mention of trade
   names or commercial products in this publication is solely for the
   purpose of providing specific information and does not imply
   recommendation or endorsement by the U.S. Department of Agriculture.}},
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Number-of-Cited-References = {{35}},
Times-Cited = {{9}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{15}},
Journal-ISO = {{Crop Sci.}},
Doc-Delivery-Number = {{984TP}},
Unique-ID = {{ISI:000307215200019}},
}

@article{ ISI:000307539600020,
Author = {Gao, Zhi-Hui and Wei, Jian-He and Yang, Yun and Zhang, Zheng and Zhao,
   Wen-Ting},
Title = {{Selection and validation of reference genes for studying stress-related
   agarwood formation of Aquilaria sinensis}},
Journal = {{PLANT CELL REPORTS}},
Year = {{2012}},
Volume = {{31}},
Number = {{9}},
Pages = {{1759-1768}},
Month = {{SEP}},
Abstract = {{Agarwood is a high-valued woody material for medicine, perfume, and
   incense production in Asia, Middle East, and Europe. The wild resources
   of agarwood-producing tree species, e.g., Aquilaria sinensis have been
   greatly threatened. The formation of agarwood is considered to be
   associated with the plant stress and defensive responses, thus it would
   be urgent and significant to investigate the molecular mechanism of
   these species responding to a variety of stresses. This is the first
   report regarding the reference gene selection of Aquilaria species for
   studying the molecular mechanism of stress-related agarwood production.
   Candidate reference genes were selected according to previous reports
   and the sequences were obtained from the 454 EST library of A. sinensis.
   To obtain the robust genes, we applied three independent programs
   depending on distinct assumptions and combined these results by a rank
   aggregation algorithm. The result supports tubulin, ribosomal protein,
   and glyceraldehyde-3-phosphate dehydrogenase to be the most stable
   reference genes for quantification of target gene expression in the
   overall samples examined. Validation of these genes through normalizing
   the expression of a terpene synthase demonstrated that these three genes
   are reliable. The selective usage of three algorithms based on their
   characteristics was underlined. However, more robust genes could be
   identified if the results of all algorithms were combined by a proper
   method such as the rank aggregation algorithm.
   Key message Reference genes which are critical in gene expression
   studies are recommended for future molecular studies of stress response
   and agarwood production in the endangered Aquilaria and other tree
   species.}},
Publisher = {{SPRINGER}},
Address = {{233 SPRING ST, NEW YORK, NY 10013 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Wei, JH (Reprint Author), Chinese Acad Med Sci, Inst Med Plant Dev, Hainan Branch, Hainan Prov Key Lab Resources Conservat \& Dev So, Wanning 571533, Peoples R China.
   Wei, Jian-He; Yang, Yun; Zhang, Zheng, Chinese Acad Med Sci, Inst Med Plant Dev, Hainan Branch, Hainan Prov Key Lab Resources Conservat \& Dev So, Wanning 571533, Peoples R China.
   Gao, Zhi-Hui; Wei, Jian-He; Zhang, Zheng; Zhao, Wen-Ting, Chinese Acad Med Sci, Inst Med Plant Dev, Beijing 100193, Peoples R China.
   Gao, Zhi-Hui; Wei, Jian-He; Zhang, Zheng; Zhao, Wen-Ting, Peking Union Med Coll, Beijing 100193, Peoples R China.}},
DOI = {{10.1007/s00299-012-1289-x}},
ISSN = {{0721-7714}},
Keywords = {{Quantitative gene expression; Reference gene; Agarwood; Aquilaria
   sinensis; Stress}},
Keywords-Plus = {{TIME RT-PCR; POLYMERASE-CHAIN-REACTION; CELL-SUSPENSION CULTURES;
   EXPRESSION ANALYSIS; QUANTITATIVE PCR; HOUSEKEEPING GENES; INTERNAL
   CONTROL; NORMALIZATION; WOOD; SESQUITERPENES}},
Research-Areas = {{Plant Sciences}},
Web-of-Science-Categories  = {{Plant Sciences}},
Author-Email = {{wjianh@263.net}},
Funding-Acknowledgement = {{National Natural Science Foundation of China {[}81001607]; Program for
   New Century Excellent Talents in University; Ministry of Education of
   China {[}2008]}},
Funding-Text = {{This study was supported by the National Natural Science Foundation of
   China (No. 81001607) and the Program for New Century Excellent Talents
   in University Funded by the Ministry of Education of China (No. 2008).}},
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Number-of-Cited-References = {{49}},
Times-Cited = {{11}},
Usage-Count-(Last-180-days) = {{5}},
Usage-Count-Since-2013 = {{21}},
Journal-ISO = {{Plant Cell Reports}},
Doc-Delivery-Number = {{989DE}},
Unique-ID = {{ISI:000307539600020}},
}

@article{ ISI:000305919800004,
Author = {Ali, Alnur and Meila, Marina},
Title = {{Experiments with Kemeny ranking: What works when?}},
Journal = {{MATHEMATICAL SOCIAL SCIENCES}},
Year = {{2012}},
Volume = {{64}},
Number = {{1, SI}},
Pages = {{28-40}},
Month = {{JUL}},
Abstract = {{This paper performs a comparison of several methods for Kemeny rank
   aggregation (104 algorithms and combinations thereof in total)
   originating in social choice theory, machine learning, and theoretical
   computer science, with the goal of establishing the best trade-offs
   between search time and performance. We find that, for this
   theoretically NP-hard task, in practice the problems span three regimes:
   strong consensus, weak consensus, and no consensus. We make specific
   recommendations for each, and propose a computationally fast test to
   distinguish between the regimes.
   In spite of the great variety of algorithms, there are few classes that
   are consistently Pareto optimal. In the most interesting regime, the
   integer program exact formulation, local search algorithms and the
   approximate version of a theoretically exact branch and bound algorithm
   arise as strong contenders. (C) 2011 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ali, A (Reprint Author), Microsoft Corp, 1 Microsoft Way, Redmond, WA 98052 USA.
   Ali, Alnur, Microsoft Corp, Redmond, WA 98052 USA.
   Meila, Marina, Univ Washington, Dept Stat, Seattle, WA 98195 USA.}},
DOI = {{10.1016/j.mathsocsci.2011.08.008}},
ISSN = {{0165-4896}},
Keywords-Plus = {{ELECTION; MODELS}},
Research-Areas = {{Business \& Economics; Mathematics; Mathematical Methods In Social
   Sciences}},
Web-of-Science-Categories  = {{Economics; Mathematics, Interdisciplinary Applications; Social Sciences,
   Mathematical Methods}},
Author-Email = {{alnurali@microsoft.com
   mmp@stat.washington.edu}},
Funding-Acknowledgement = {{NSF {[}IIS-0535100]}},
Funding-Text = {{We thank the anonymous reviewers for the constructive feedback that
   significantly improved this paper. MM acknowledges partial support from
   NSF award IIS-0535100.}},
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Number-of-Cited-References = {{31}},
Times-Cited = {{8}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{Math. Soc. Sci.}},
Doc-Delivery-Number = {{967PH}},
Unique-ID = {{ISI:000305919800004}},
}

@article{ ISI:000305338900053,
Author = {Liu, Qi and Zhou, Han and Cui, Juan and Cao, Zhiwei and Xu, Ying},
Title = {{Reconsideration of In-Silico siRNA Design Based on Feature Selection: A
   Cross-Platform Data Integration Perspective}},
Journal = {{PLOS ONE}},
Year = {{2012}},
Volume = {{7}},
Number = {{5}},
Month = {{MAY 24}},
Abstract = {{RNA interference via exogenous short interference RNAs (siRNA) is
   increasingly more widely employed as a tool in gene function studies,
   drug target discovery and disease treatment. Currently there is a strong
   need for rational siRNA design to achieve more reliable and specific
   gene silencing; and to keep up with the increasing needs for a wider
   range of applications. While progress has been made in the ability to
   design siRNAs with specific targets, we are clearly at an infancy stage
   towards achieving rational design of siRNAs with high efficacy. Among
   the many obstacles to overcome, lack of general understanding of what
   sequence features of siRNAs may affect their silencing efficacy and of
   large-scale homogeneous data needed to carry out such association
   analyses represents two challenges. To address these issues, we
   investigated a feature-selection based in-silico siRNA design from a
   novel cross-platform data integration perspective. An integration
   analysis of 4,482 siRNAs from ten meta-datasets was conducted for
   ranking siRNA features, according to their possible importance to the
   silencing efficacy of siRNAs across heterogeneous data sources. Our
   ranking analysis revealed for the first time the most relevant features
   based on cross-platform experiments, which compares favorably with the
   traditional in-silico siRNA feature screening based on the small samples
   of individual platform data. We believe that our feature ranking
   analysis can offer more creditable suggestions to help improving the
   design of siRNA with specific silencing targets. Data and scripts are
   available at
   http://csbl.bmb.uga.edu/publications/materials/qiliu/siRNA.html.}},
Publisher = {{PUBLIC LIBRARY SCIENCE}},
Address = {{1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Liu, Q (Reprint Author), Tongji Univ, Dept Bioinformat, Shanghai 200092, Peoples R China.
   Liu, Qi; Zhou, Han; Cao, Zhiwei, Tongji Univ, Dept Bioinformat, Shanghai 200092, Peoples R China.
   Cui, Juan; Xu, Ying, Univ Georgia, Dept Biochem \& Mol Biol, Computat Syst Biol Lab, Athens, GA 30602 USA.
   Cui, Juan; Xu, Ying, Univ Georgia, Inst Bioinformat, Athens, GA 30602 USA.
   Xu, Ying, Jilin Univ, Coll Comp Sci \& Technol, Changchun 130023, Peoples R China.}},
DOI = {{10.1371/journal.pone.0037879}},
Article-Number = {{e37879}},
ISSN = {{1932-6203}},
Keywords-Plus = {{DOUBLE-STRANDED-RNA; WEIGHTED RANK AGGREGATION; SUPPORT VECTOR MACHINE;
   MESSENGER-RNA; EFFICACY PREDICTION; FUNCTIONAL SIRNAS; INTERFERING RNAS;
   CANCER-THERAPY; MONTE-CARLO; EFFICIENT}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
Author-Email = {{zwcao@tongji.edu.cn
   xyn@bmb.uga.edu}},
Funding-Acknowledgement = {{Project White Magnolia Funding, Shanghai {[}2010B127]; Shanghai Pujiang
   Talents Funding {[}11PJ1407400]; Tongji Excellent Young Scientist
   Funding {[}2000219052]; National Natural Science Foundation of China
   {[}30976611, 31100956, 61173117]; Young Teachers for the Doctoral
   Program of Ministry of Education, China {[}20110072120048]}},
Funding-Text = {{1. Project White Magnolia Funding, Shanghai (Grant No. 2010B127)
   http://www.stcsm.gov.cn/structure/index.htm, 2. Shanghai Pujiang Talents
   Funding (Grant No. 11PJ1407400)
   http://www.stcsm.gov.cn/structure/index.htm, 3. Tongji Excellent Young
   Scientist Funding (Grant No. 2000219052) http://www.tongji.edu.cn/, 4.
   National Natural Science Foundation of China (Grant No. 30976611, Grant
   No. 31100956 and Grant No.
   61173117)http://www.nsfc.gov.cn/Portal0/default152.htm, 5. Young
   Teachers for the Doctoral Program of Ministry of Education, China (Grant
   No. 20110072120048) http://www.moe.edu.cn/. The funders had no role in
   study design, data collection and analysis, decision to publish, or
   preparation of the manuscript.}},
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Number-of-Cited-References = {{39}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{11}},
Journal-ISO = {{PLoS One}},
Doc-Delivery-Number = {{959UB}},
Unique-ID = {{ISI:000305338900053}},
}

@article{ ISI:000301293900026,
Author = {Sengupta, Debarka and Maulik, Ujjwal and Bandyopadhyay, Sanghamitra},
Title = {{Weighted Markov Chain Based Aggregation of Biomolecule Orderings}},
Journal = {{IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS}},
Year = {{2012}},
Volume = {{9}},
Number = {{3}},
Pages = {{924-933}},
Month = {{MAY-JUN}},
Abstract = {{The scope and effectiveness of Rank Aggregation (RA) have already been
   established in contemporary bioinformatics research. Rank aggregation
   helps in meta-analysis of putative results collected from different
   analytic or experimental sources. For example, we often receive
   considerably differing ranked lists of genes or microRNAs from various
   target prediction algorithms or microarray studies. Sometimes combining
   them all, in some sense, yields more effective ordering of the set of
   objects. Also, assigning a certain level of confidence to each source of
   ranking is a natural demand of aggregation. Assignment of weights to the
   sources of orderings can be performed by experts. Several rank
   aggregation approaches like those based on Markov Chains (MCs),
   evolutionary algorithms, etc., exist in the literature. Markov chains,
   in general, are faster than the evolutionary approaches. Unlike the
   evolutionary computing approaches Markov chains have not been used for
   weighted aggregation scenarios. This is because of the absence of a
   formal framework of Weighted Markov Chain (WMC). In this paper, we
   propose the use of a modified version of MC4 (one of the Markov chains
   proposed by Dwork et al., 2001), followed by the weighted analog of
   local Kemenization for performing rank aggregation, where the sources of
   rankings can be prioritized by an expert. Effectiveness of the weighted
   Markov chain approach over the very recently proposed Genetic Algorithm
   (GA) and Cross-Entropy Monte Carlo (MC) algorithm-based techniques, has
   been established for gene orderings from microarray analysis and
   orderings of predicted microRNA targets.}},
Publisher = {{IEEE COMPUTER SOC}},
Address = {{10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Sengupta, D (Reprint Author), Indian Stat Inst, Machine Intelligence Unit, DST Sponsored Project, Kolkata, India.
   Sengupta, Debarka, Indian Stat Inst, Machine Intelligence Unit, DST Sponsored Project, Kolkata, India.
   Maulik, Ujjwal, Jadavpur Univ, Dept Comp Sci, Kolkata, India.
   Maulik, Ujjwal, Jadavpur Univ, Dept Comp Sci \& Technol, Kolkata, India.}},
DOI = {{10.1109/TCBB.2012.28}},
ISSN = {{1545-5963}},
EISSN = {{1557-9964}},
Keywords = {{Rank aggregation; Markov chain; Kendall's tau; microRNA; genes; ordering}},
Keywords-Plus = {{MAMMALIAN MICRORNA TARGETS; PROSTATE-CANCER; RANK AGGREGATION;
   MONTE-CARLO; PREDICTION; IDENTIFICATION; LISTS}},
Research-Areas = {{Biochemistry \& Molecular Biology; Computer Science; Mathematics}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Computer Science, Interdisciplinary
   Applications; Mathematics, Interdisciplinary Applications; Statistics \&
   Probability}},
Author-Email = {{debarka\_r@isical.ac.in
   umaulik@cse.jdvu.ac.in
   sanghami@isical.ac.in}},
Funding-Acknowledgement = {{Swarnajayanti Fellowship scheme of the Department of Science and
   Technology, Government of India {[}DST/SJF/ET-02/2006-07]}},
Funding-Text = {{D.S. and S.B. gratefully acknowledge the financial support from the
   grant no. DST/SJF/ET-02/2006-07 under the Swarnajayanti Fellowship
   scheme of the Department of Science and Technology, Government of India.}},
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Number-of-Cited-References = {{38}},
Times-Cited = {{6}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{8}},
Journal-ISO = {{IEEE-ACM Trans. Comput. Biol. Bioinform.}},
Doc-Delivery-Number = {{905SM}},
Unique-ID = {{ISI:000301293900026}},
}

@article{ ISI:000303364100003,
Author = {Streib, Noah and Young, Stephen J. and Sokol, Joel},
Title = {{A Major League Baseball Team Uses Operations Research to Improve Draft
   Preparation}},
Journal = {{INTERFACES}},
Year = {{2012}},
Volume = {{42}},
Number = {{2}},
Pages = {{119-130}},
Month = {{MAR-APR}},
Abstract = {{Preparing for the annual major league baseball draft is a difficult
   task; with 1,500 players selected each year, teams must evaluate and
   rank many hundreds of potential draftees. To evaluate the players, these
   teams send out scouts, baseball experts who make qualitative and
   quantitative observations and report their opinions to the team.
   However, scouts often disagree significantly in their opinions. We
   worked with a major league team to model and solve the problem of
   suggesting a consensus ranking of all players scouted by the team's
   representatives. Our methodology can also make in-season recommendations
   for dynamic scout scheduling based on the level of information each
   scout is likely to provide on each player, and the uncertainty in the
   ``correct{''} overall ranking of each player. The team has been using
   the optimization tool we provided for the past two years, and a second
   major league team has also asked us to evaluate its ranking data.}},
Publisher = {{INFORMS}},
Address = {{7240 PARKWAY DR, STE 310, HANOVER, MD 21076-1344 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Streib, N (Reprint Author), Georgia Inst Technol, Sch Math, Atlanta, GA 30332 USA.
   Streib, Noah, Georgia Inst Technol, Sch Math, Atlanta, GA 30332 USA.
   Young, Stephen J., Univ Calif San Diego, Dept Math, La Jolla, CA 92093 USA.
   Sokol, Joel, Georgia Inst Technol, H Milton Stewart Sch Ind \& Syst Engn, Atlanta, GA 30332 USA.}},
DOI = {{10.1287/inte.1100.0552}},
ISSN = {{0092-2102}},
Keywords = {{major league baseball; voting/committees: games/group decisions;
   recreation/sports; decision support systems; information systems}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
Author-Email = {{nstreib3@math.gatech.edu
   s7young@math.ucsd.edu
   jsokol@isye.gatech.edu}},
Cited-References = {{KEMENY JG, 1959, DAEDALUS, V88, P577.
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Number-of-Cited-References = {{16}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{9}},
Journal-ISO = {{Interfaces}},
Doc-Delivery-Number = {{933LW}},
Unique-ID = {{ISI:000303364100003}},
}

@article{ ISI:000301884400018,
Author = {Kang, Hong and Sheng, Zhen and Zhu, Ruixin and Huang, Qi and Liu, Qi and
   Cao, Zhiwei},
Title = {{Virtual Drug Screen Schema Based on Multiview Similarity Integration and
   Ranking Aggregation}},
Journal = {{JOURNAL OF CHEMICAL INFORMATION AND MODELING}},
Year = {{2012}},
Volume = {{52}},
Number = {{3}},
Pages = {{834-843}},
Month = {{MAR}},
Abstract = {{The current drug virtual screen (VS) methods mainly include two
   categories. i.e., ligand/target structure-based virtual screen and that,
   utilizing protein ligand interaction fingerprint information based on
   the large number of complex structures. Since the former one focuses on
   the one-side information while the later one focuses on the whole
   complex structure, they are thus complementary and can be boosted by
   each other. However, a common problem faced here is how to present a
   comprehensive understanding and evaluation of the various virtual screen
   results derived from various VS methods. Furthermore, there is still an
   urgent need for developing an efficient approach to fully integrate
   various VS methods from a comprehensive multiview perspective. In this
   study, our virtual screen schema based on multiview similarity
   integration and ranking aggregation was tested comprehensively with
   statistical evaluations, providing several novel and useful clues on how
   to perform drug VS from multiple heterogeneous data sources. (1) 18
   complex structures of HIV-1 protease with ligands from the PDB were
   curated as a test data set and the VS was performed with five different
   drug representations. Ritonavir (1HXW) was selected as the query in VS
   and the weighted ranks of the query results were aggregated from
   multiple views through four similarity integration approaches. (2)
   Further, one of the ranking aggregation methods was used to integrate
   the similarity ranks calculated by gene ontology (GO) fingerprint and
   structural fingerprint on the data set from connectivity map, and two
   typical HDAC and HSP90 inhibitors were chosen as the queries. The
   results show that rank aggregation can enhance the result of similarity
   searching in VS when two or more descriptions are involved and provide a
   more reasonable similarity rank result. Our study shows that integrated
   VS based on multiple data fusion can achieve a remarkable better
   performance compared to that from individual ones and, thus, serves as a
   promising way for efficient drug screening, taking advantages of the
   rapidly accumulated molecule representations and heterogeneous data in
   the pharmacological area.}},
Publisher = {{AMER CHEMICAL SOC}},
Address = {{1155 16TH ST, NW, WASHINGTON, DC 20036 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Liu, Q (Reprint Author), Tongji Univ, Sch Life Sci \& Technol, Shanghai 200092, Peoples R China.
   Kang, Hong; Sheng, Zhen; Zhu, Ruixin; Huang, Qi; Liu, Qi; Cao, Zhiwei, Tongji Univ, Sch Life Sci \& Technol, Shanghai 200092, Peoples R China.}},
DOI = {{10.1021/ci200481c}},
ISSN = {{1549-9596}},
Keywords-Plus = {{HIV-1 PROTEASE-INHIBITOR; IMMUNODEFICIENCY VIRUS-1 PROTEASE; ORALLY
   BIOAVAILABLE INHIBITOR; UNEXPECTED BINDING MODE; STRUCTURE-BASED DESIGN;
   CRYSTAL-STRUCTURE; MOLECULAR DOCKING; IN-VITRO; CHEMICAL SIMILARITY;
   HSP90 INHIBITORS}},
Research-Areas = {{Pharmacology \& Pharmacy; Chemistry; Computer Science}},
Web-of-Science-Categories  = {{Chemistry, Medicinal; Chemistry, Multidisciplinary; Computer Science,
   Information Systems; Computer Science, Interdisciplinary Applications}},
Author-Email = {{qiliu@tongji.edu.cn
   zwcao@tongji.edu.cn}},
Funding-Acknowledgement = {{Ministry of Science and Technology China {[}2010CB833601]; National
   Natural Science Foundation of China {[}31171272, 31100956, 61173117];
   Research Fund for the Doctoral Program of Higher Education of China
   {[}20100072110008, 20110072120048]; Shanghai Pujiang talent funding
   {[}11PJ1407400]}},
Funding-Text = {{This work was supported in part by grants from Ministry of Science and
   Technology China (2010CB833601), National Natural Science Foundation of
   China (31171272, 31100956, and 61173117), Research Fund for the Doctoral
   Program of Higher Education of China (20100072110008, 20110072120048),
   and Shanghai Pujiang talent funding (11PJ1407400).}},
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Number-of-Cited-References = {{84}},
Times-Cited = {{9}},
Usage-Count-(Last-180-days) = {{3}},
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Journal-ISO = {{J. Chem Inf. Model.}},
Doc-Delivery-Number = {{913NJ}},
Unique-ID = {{ISI:000301884400018}},
}

@article{ ISI:000300490500017,
Author = {Kolde, Raivo and Laur, Sven and Adler, Priit and Vilo, Jaak},
Title = {{Robust rank aggregation for gene list integration and meta-analysis}},
Journal = {{BIOINFORMATICS}},
Year = {{2012}},
Volume = {{28}},
Number = {{4}},
Pages = {{573-580}},
Month = {{FEB 15}},
Abstract = {{Motivation: The continued progress in developing technological
   platforms, availability of many published experimental datasets, as well
   as different statistical methods to analyze those data have allowed
   approaching the same research question using various methods
   simultaneously. To get the best out of all these alternatives, we need
   to integrate their results in an unbiased manner. Prioritized gene lists
   are a common result presentation method in genomic data analysis
   applications. Thus, the rank aggregation methods can become a useful and
   general solution for the integration task.
   Results: Standard rank aggregation methods are often ill-suited for
   biological settings where the gene lists are inherently noisy. As a
   remedy, we propose a novel robust rank aggregation (RRA) method. Our
   method detects genes that are ranked consistently better than expected
   under null hypothesis of uncorrelated inputs and assigns a significance
   score for each gene. The underlying probabilistic model makes the
   algorithm parameter free and robust to outliers, noise and errors.
   Significance scores also provide a rigorous way to keep only the
   statistically relevant genes in the final list. These properties make
   our approach robust and compelling for many settings.}},
Publisher = {{OXFORD UNIV PRESS}},
Address = {{GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Vilo, J (Reprint Author), Univ Tartu, Inst Comp Sci, Liivi 2-314, EE-50409 Tartu, Estonia.
   Kolde, Raivo; Laur, Sven; Adler, Priit; Vilo, Jaak, Univ Tartu, Inst Comp Sci, EE-50409 Tartu, Estonia.
   Kolde, Raivo; Vilo, Jaak, Quretec, EE-51003 Tartu, Estonia.
   Adler, Priit, Univ Tartu, Inst Mol \& Cell Biol, EE-51010 Tartu, Estonia.}},
DOI = {{10.1093/bioinformatics/btr709}},
ISSN = {{1367-4803}},
Keywords-Plus = {{SACCHAROMYCES-CEREVISIAE; MICROARRAY EXPERIMENTS; EXPRESSION PROFILES;
   GENOMIC DATA; CANCER; COEXPRESSION; NETWORK; VALIDATION; REVEALS;
   ARCHIVE}},
Research-Areas = {{Biochemistry \& Molecular Biology; Biotechnology \& Applied
   Microbiology; Computer Science; Mathematical \& Computational Biology;
   Mathematics}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Biotechnology \& Applied Microbiology;
   Computer Science, Interdisciplinary Applications; Mathematical \&
   Computational Biology; Statistics \& Probability}},
Author-Email = {{vilo@ut.ee}},
ResearcherID-Numbers = {{Vilo, Jaak/A-7183-2008
   }},
ORCID-Numbers = {{Vilo, Jaak/0000-0001-5604-4107
   Kolde, Raivo/0000-0003-2886-6298}},
Funding-Acknowledgement = {{Tiger University of the Estonian Information Technology Foundation; EU
   {[}LSHG-CT-2005-518254]; ESNATS {[}HEALTH-F5-2008-201619]; European
   Regional Development Fund through the Estonian Centre of Excellence in
   Computer Science project; Estonian Science Foundation {[}ETF7437]}},
Funding-Text = {{Tiger University Program of the Estonian Information Technology
   Foundation. EU FP6 and FP7 projects ENFIN (LSHG-CT-2005-518254); ESNATS
   (HEALTH-F5-2008-201619); European Regional Development Fund through the
   Estonian Centre of Excellence in Computer Science project and Estonian
   Science Foundation (ETF7437, CIESCI).}},
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Number-of-Cited-References = {{28}},
Times-Cited = {{37}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{13}},
Journal-ISO = {{Bioinformatics}},
Doc-Delivery-Number = {{895IT}},
Unique-ID = {{ISI:000300490500017}},
}

@article{ ISI:000310124100006,
Author = {Sadeghi, Hamid},
Title = {{Empirical challenges and solutions in constructing a high-performance
   metasearch engine}},
Journal = {{ONLINE INFORMATION REVIEW}},
Year = {{2012}},
Volume = {{36}},
Number = {{5}},
Pages = {{713-723}},
Abstract = {{Purpose - This paper seeks to disclose the important role of missing
   documents, broken links and duplicate items in the results merging
   process of a metasearch engine in detail. It aims to investigate some
   related practical challenges and proposes some solutions. The study also
   aims to employ these solutions to improve an existing model for results
   aggregation.
   Design/methodology/approach - This research measures the amount of an
   increase in retrieval effectiveness of an existing results merging model
   that is obtained as a result of the proposed improvements. The 50
   queries of the 2002 TREC web track were employed as a standard test
   collection based on a snapshot of the worldwide web to explore and
   evaluate the retrieval effectiveness of the suggested method. Three
   popular web search engines (Ask, Bing and Google) as the underlying
   resources of metasearch engines were selected. Each of the 50 queries
   was passed to all three search engines. For each query the top ten
   non-sponsored results of each search engine were retrieved. The returned
   result lists of the search engines were aggregated using a proposed
   algorithm that takes the practical issues of the process into
   consideration. The effectiveness of the result lists generated was
   measured using a well-known performance indicator called ``TSAP{''}
   (TREC-style average precision).
   Findings - Experimental results demonstrate that the proposed model
   increases the performance of an existing results merging system by 14.39
   percent on average.
   Practical implications - The findings of this research would be helpful
   for metasearch engine designers as well as providing motivation to the
   vendors of web search engines to improve their technology.
   Originality/value - This study provides some valuable concepts,
   practical challenges, solutions and experimental results in the field of
   web metasearching that have not been previously investigated.}},
Publisher = {{EMERALD GROUP PUBLISHING LTD}},
Address = {{HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Sadeghi, H (Reprint Author), Islamic Azad Univ, Dept Comp Engn, Hashtgerd Branch, Alborz, Iran.
   Islamic Azad Univ, Dept Comp Engn, Hashtgerd Branch, Alborz, Iran.}},
DOI = {{10.1108/14684521211275993}},
ISSN = {{1468-4527}},
EISSN = {{1468-4535}},
Keywords = {{Metasearch; Missing documents; Broken links; Duplicate documents; Data
   fusion; Rank aggregation; OWA operator; Searching; Information searches;
   Information retrieval}},
Keywords-Plus = {{WEB SEARCH ENGINES; AGGREGATION OPERATORS; INFORMATION-RETRIEVAL; FUSION}},
Research-Areas = {{Computer Science; Information Science \& Library Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Information Science \& Library
   Science}},
Author-Email = {{hisadeghi@gmail.com}},
Funding-Acknowledgement = {{Hashtgerd Branch, Islamic Azad University}},
Funding-Text = {{The author would like to thank Hashtgerd Branch, Islamic Azad University
   for financial support for this research.}},
Cited-References = {{Amin GR, 2010, J OPER RES SOC, V61, P1144, DOI 10.1057/jors.2009.53.
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Number-of-Cited-References = {{30}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{22}},
Journal-ISO = {{Online Inf. Rev.}},
Doc-Delivery-Number = {{024QQ}},
Unique-ID = {{ISI:000310124100006}},
}

@article{ ISI:000308075600013,
Author = {Dohi, O. and Yagi, N. and Wada, T. and Yamada, N. and Bito, N. and
   Yamada, S. and Gen, Y. and Yoshida, N. and Uchiyama, K. and Ishikawa, T.
   and Takagi, T. and Handa, O. and Konishi, H. and Wakabayashi, N. and
   Kokura, S. and Naito, Y. and Yoshikawa, T.},
Title = {{Recognition of Endoscopic Diagnosis in Differentiated-Type Early Gastric
   Cancer by Flexible Spectral Imaging Color Enhancement with Indigo
   Carmine}},
Journal = {{DIGESTION}},
Year = {{2012}},
Volume = {{86}},
Number = {{2}},
Pages = {{161-170}},
Abstract = {{Background/Aims: To evaluate the usefulness of flexible spectral imaging
   color enhancement with indigo carmine (I-FICE) in early gastric cancer
   (EGC) demarcation. Methods: The study participants were 29 patients with
   differentiated-type EGC. The endoscope was fixed and images of the same
   area of EGC demarcations in each lesion were obtained using four
   different methods (WLE, flexible spectral imaging color enhancement
   (FICE), CE, and I-FICE). FICE mode at R 550 nm (Gain: 2), G 500 nm
   (Gain: 4), and B 470 nm (Gain: 4) was used. Four endoscopists ranked the
   images obtained by each method on the basis of the ease of recognition
   of demarcation using a 4-point system. We calculated the standard
   deviation of pixel values based on L{*}, a{*}, and b{*} color spaces in
   the demarcation region (Lab-SD score). Results: The median ranking score
   for I-FICE images was significantly higher than that obtained from the
   other methods. Further, the average Lab-SD score was significantly
   higher for I-FICE images than for images obtained by the other methods.
   There was a good correlation between the ranking score and Lab-SD score.
   Conclusion: EGC demarcations were most easily recognized both
   subjectively and objectively using I-FICE image, followed by CE, FICE
   and WLE images. Copyright (c) 2012 S. Karger AG, Basel}},
Publisher = {{KARGER}},
Address = {{ALLSCHWILERSTRASSE 10, CH-4009 BASEL, SWITZERLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Dohi, O (Reprint Author), Kyoto Prefectural Univ Med, Grad Sch Med Sci, Dept Mol Gastroenterol \& Hepatol, Kamigyo Ku, 465 Kawaramachi Hirokoji, Kyoto 6028566, Japan.
   Dohi, O., Kyoto Prefectural Univ Med, Grad Sch Med Sci, Dept Mol Gastroenterol \& Hepatol, Kamigyo Ku, Kyoto 6028566, Japan.}},
DOI = {{10.1159/000339878}},
ISSN = {{0012-2823}},
Keywords = {{Differentiated-type early gastric cancer; Early gastric cancer; EGC
   demarcations; Endoscopic diagnosis; Endoscopic submucosal dissection;
   Flexible spectral imaging color enhancement}},
Keywords-Plus = {{COMPUTED VIRTUAL CHROMOENDOSCOPY; MUCOSAL RESECTION; SYSTEM}},
Research-Areas = {{Gastroenterology \& Hepatology}},
Web-of-Science-Categories  = {{Gastroenterology \& Hepatology}},
Author-Email = {{osamu-d@koto.kpu-m.ac.jp}},
Cited-References = {{IDA K, 1975, AM J GASTROENTEROL, V63, P316.
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Number-of-Cited-References = {{19}},
Times-Cited = {{6}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{Digestion}},
Doc-Delivery-Number = {{996HN}},
Unique-ID = {{ISI:000308075600013}},
}

@article{ ISI:000304853800017,
Author = {Schimek, Michael G. and Mysickova, Alena and Budinska, Eva},
Title = {{An Inference and Integration Approach for the Consolidation of Ranked
   Lists}},
Journal = {{COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION}},
Year = {{2012}},
Volume = {{41}},
Number = {{7, SI}},
Pages = {{1152-1166}},
Note = {{6th St Petersburg Workshop on Simulation, St Petersburg, RUSSIA, JUN
   28-JUL 03, 2009}},
Organization = {{St Petersburg State Univ, Dept Stochast Simulat}},
Abstract = {{In this article, we describe a new approach that combines the estimation
   of the lengths of highly conforming sublists with their stochastic
   aggregation, to deal with two or more rankings of the same set of
   objects. The goal is to obtain a much smaller set of informative common
   objects in a new rank order. The input lists can be of large or huge
   size, their rankings irregular and incomplete due to random and missing
   assignments. A moderate deviation-based inference procedure and a
   cross-entropy Monte Carlo technique are used to handle the combinatorial
   complexity of the task. Two alternative distance measures are considered
   that can accommodate truncated list information. Finally, the outlined
   approach is applied to simulated data that was motivated by microarray
   meta-analysis, an important field of application.}},
Publisher = {{TAYLOR \& FRANCIS INC}},
Address = {{325 CHESTNUT ST, SUITE 800, PHILADELPHIA, PA 19106 USA}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Schimek, MG (Reprint Author), Med Univ Graz, Inst Med Informat Stat \& Documentat, Auenbruggerpl 2-V, A-8036 Graz, Austria.
   Schimek, Michael G., Med Univ Graz, Inst Med Informat Stat \& Documentat, A-8036 Graz, Austria.
   Mysickova, Alena, Max Planck Inst Mol Genet, D-14195 Berlin, Germany.
   Budinska, Eva, Swiss Inst Bioinformat, Lausanne, Switzerland.
   Budinska, Eva, Masaryk Univ, Inst Biostat \& Anal, Brno, Czech Republic.}},
DOI = {{10.1080/03610918.2012.625843}},
ISSN = {{0361-0918}},
Keywords = {{Cross-entropy Monte Carlo; Kendall's tau; Moderate deviation; Partial
   list; Random degeneration; Rank aggregation; Spearman's footrule; Top-k
   ranked list}},
Keywords-Plus = {{RANKING MODELS; AGGREGATION}},
Research-Areas = {{Mathematics}},
Web-of-Science-Categories  = {{Statistics \& Probability}},
Author-Email = {{michael.schimek@medunigraz.at}},
ResearcherID-Numbers = {{Budinska, Eva/F-2698-2011}},
ORCID-Numbers = {{Budinska, Eva/0000-0002-9004-9187}},
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   Schimek M. G., STAT INTEGR IN PRESS.}},
Number-of-Cited-References = {{23}},
Times-Cited = {{3}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{8}},
Journal-ISO = {{Commun. Stat.-Simul. Comput.}},
Doc-Delivery-Number = {{953GB}},
Unique-ID = {{ISI:000304853800017}},
}

@article{ ISI:000303726000001,
Author = {Qi, Jianlong and Michoel, Tom and Butler, Gregory},
Title = {{An Integrative Approach to Infer Regulation Programs in a Transcription
   Regulatory Module Network}},
Journal = {{JOURNAL OF BIOMEDICINE AND BIOTECHNOLOGY}},
Year = {{2012}},
Abstract = {{The module network method, a special type of Bayesian network
   algorithms, has been proposed to infer transcription regulatory networks
   from gene expression data. In this method, a module represents a set of
   genes, which have similar expression profiles and are regulated by same
   transcription factors. The process of learning module networks consists
   of two steps: first clustering genes into modules and then inferring the
   regulation program ( transcription factors) of each module. Many
   algorithms have been designed to infer the regulation program of a given
   gene module, and these algorithms show very different biases in
   detecting regulatory relationships. In this work, we explore the
   possibility of integrating results from different algorithms. The
   integration methods we select are union, intersection, and weighted rank
   aggregation. Experiments in a yeast dataset show that the union and
   weighted rank aggregation methods produce more accurate predictions than
   those given by individual algorithms, whereas the intersection method
   does not yield any improvement in the accuracy of predictions. In
   addition, somewhat surprisingly, the union method, which has a lower
   computational cost than rank aggregation, achieves comparable results as
   given by rank aggregation.}},
Publisher = {{HINDAWI PUBLISHING CORPORATION}},
Address = {{410 PARK AVENUE, 15TH FLOOR, \#287 PMB, NEW YORK, NY 10022 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Butler, G (Reprint Author), Concordia Univ, Dept Comp Sci \& Software Engn, 1455 Maisonneuve Blvd W, Montreal, PQ H3G 1M8, Canada.
   Butler, Gregory, Concordia Univ, Dept Comp Sci \& Software Engn, Montreal, PQ H3G 1M8, Canada.
   Qi, Jianlong; Michoel, Tom, Univ Freiburg, Freiburg Inst Adv Studies, D-79104 Freiburg, Germany.}},
DOI = {{10.1155/2012/245968}},
Article-Number = {{245968}},
ISSN = {{1110-7243}},
Keywords-Plus = {{GENE-EXPRESSION DATA; SACCHAROMYCES-CEREVISIAE}},
Research-Areas = {{Biotechnology \& Applied Microbiology; Research \& Experimental Medicine}},
Web-of-Science-Categories  = {{Biotechnology \& Applied Microbiology; Medicine, Research \&
   Experimental}},
Author-Email = {{gregb@encs.concordia.ca}},
Cited-References = {{Gasch AP, 2000, MOL BIOL CELL, V11, P4241.
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   Monteiro PT, 2008, NUCLEIC ACIDS RES, V36, pD132, DOI 10.1093/nar/gkm976.
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   Stolovitzky G, 2009, ANN NY ACAD SCI, V1158, P159, DOI 10.1111/j.1749-6632.2009.04497.x.}},
Number-of-Cited-References = {{24}},
Times-Cited = {{3}},
Usage-Count-(Last-180-days) = {{5}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{J. Biomed. Biotechnol.}},
Doc-Delivery-Number = {{938IA}},
Unique-ID = {{ISI:000303726000001}},
}

@article{ ISI:000209435700040,
Author = {Modzelewski, Romain and Janvresse, Elise and de la Rue, Thierry and
   Vera, Pierre},
Title = {{Comparison of heterogeneity quantification algorithms for brain SPECT
   perfusion images}},
Journal = {{EJNMMI RESEARCH}},
Year = {{2012}},
Volume = {{2}},
Abstract = {{Background: Several algorithms from the literature were compared with
   the original random walk (RW) algorithm for brain perfusion
   heterogeneity quantification purposes. Algorithms are compared on a set
   of 210 brain single photon emission computed tomography (SPECT)
   simulations and 40 patient exams.
   Methods: Five algorithms were tested on numerical phantoms. The
   numerical anthropomorphic Zubal head phantom was used to generate 42 (6
   x 7) different brain SPECT simulations. Seven diffuse cortical
   heterogeneity levels were simulated with an adjustable Gaussian noise
   function and six focal perfusion defect levels with temporoparietal (TP)
   defects. The phantoms were successively projected and smoothed with
   Gaussian kernel with full width at half maximum (FWHM = 5 mm), and
   Poisson noise was added to the 64 projections. For each simulation, 5
   Poisson noise realizations were performed yielding a total of 210
   datasets. The SPECT images were reconstructed using filtered black
   projection (Hamming filter: alpha = 0.5).
   The five algorithms or measures tested were the following: the
   coefficient of variation, the entropy and local entropy, fractal
   dimension (FD) (box counting and Fourier power spectrum methods), the
   gray-level co-occurrence matrix (GLCM), and the new RW.
   The heterogeneity discrimination power was obtained with a linear
   regression for each algorithm. This regression line is a mean function
   of the measure of heterogeneity compared to the different diffuse
   heterogeneity and focal defect levels generated in the phantoms. A
   greater slope denotes a larger separation between the levels of diffuse
   heterogeneity.
   The five algorithms were computed using 40 99mTc-ethyl-cysteinate-dimer
   (ECD) SPECT images of patients referred for memory impairment. Scans
   were blindly ranked by two physicians according to the level of
   heterogeneity, and a consensus was obtained. The rankings obtained by
   the algorithms were compared with the physicians' consensus ranking.
   Results: The GLCM method (slope = 58.5), the fractal dimension (35.9),
   and the RW method (31.6) can differentiate the different levels of
   diffuse heterogeneity. The GLCM contrast parameter method is not
   influenced by a focal defect contrary to the FD and RW methods. A
   significant correlation was found between the RW method and the
   physicians' classification (r = 0.86; F = 137; p < 0.0001).
   Conclusions: The GLCM method can quantify the different levels of
   diffuse heterogeneity in brain-simulated SPECT images without an
   influence from the focal cortical defects. However, GLCM classification
   was not correlated with the physicians' classification (Rho = -0.099).
   The RW method was significantly correlated with the physicians'
   heterogeneity perception but is influenced by the existence of a focal
   defect.}},
Publisher = {{SPRINGER HEIDELBERG}},
Address = {{TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Modzelewski, R (Reprint Author), Univ Rouen, Fac Med, QUANT IF Quantificat Imagerie Fonct, Lab Informat Traitement Informat \& Syst EA LITIS, F-76801 St Etienne, France.
   Modzelewski, Romain; Vera, Pierre, Univ Rouen, Fac Med, QUANT IF Quantificat Imagerie Fonct, Lab Informat Traitement Informat \& Syst EA LITIS, F-76801 St Etienne, France.
   Modzelewski, Romain; Vera, Pierre, Ctr Henri Becquerel, Dept Nucl Med, F-76000 Rouen, France.
   Modzelewski, Romain; Vera, Pierre, Rouen Univ Hosp, F-76000 Rouen, France.
   Janvresse, Elise; de la Rue, Thierry, Raphael Salem Math Lab, UMR CNRS 6085, F-76801 St Etienne, France.}},
DOI = {{10.1186/2191-219X-2-40}},
Article-Number = {{40}},
ISSN = {{2191-219X}},
Keywords = {{Heterogeneity; Quantification; Functional imaging; Brain; Single photon
   emission computed tomography; Perfusion}},
Research-Areas = {{Radiology, Nuclear Medicine \& Medical Imaging}},
Web-of-Science-Categories  = {{Radiology, Nuclear Medicine \& Medical Imaging}},
Author-Email = {{romain.modzelewski@chb.unicancer.fr}},
ORCID-Numbers = {{de la Rue, Thierry/0000-0002-1504-5792}},
Funding-Acknowledgement = {{Comite de Seine-Maritime de la Ligue Contre le Cancer}},
Funding-Text = {{This work was partially supported by grants from the `Comite de
   Seine-Maritime de la Ligue Contre le Cancer'.}},
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Number-of-Cited-References = {{52}},
Times-Cited = {{3}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{EJNMMI Res.}},
Doc-Delivery-Number = {{V39UK}},
Unique-ID = {{ISI:000209435700040}},
}

@article{ ISI:000293683500002,
Author = {Li, Lin and Xu, Guandong and Zhang, Yanchun and Kitsuregawa, Masaru},
Title = {{Random walk based rank aggregation to improving web search}},
Journal = {{KNOWLEDGE-BASED SYSTEMS}},
Year = {{2011}},
Volume = {{24}},
Number = {{7}},
Pages = {{943-951}},
Month = {{OCT}},
Abstract = {{In Web search, with the aid of related query recommendation, Web users
   can revise their initial queries in several serial rounds in pursuit of
   finding needed Web pages. In this paper, we address the Web search
   problem on aggregating search results of related queries to improve the
   retrieval quality. Given an initial query and the suggested related
   queries, our search system concurrently processes their search result
   lists from an existing search engine and then forms a single list
   aggregated by all the retrieved lists. We specifically propose a generic
   rank aggregation framework which consists of three steps. First we build
   a so-called Win/Loss graph of Web pages according to a competition rule,
   and then apply the random walk mechanism on the Win/Loss graph. Last we
   sort these Web pages by their ranks using a PageRank-like rank
   mechanism. The proposed framework considers not only the number of wins
   that an item won in competitions, but also the quality of its competitor
   items in calculating the ranking of Web page items. Experimental results
   show that our search system can clearly improve the retrieval quality in
   a parallel manner over the traditional search strategy that serially
   returns result lists. Moreover, we also provide empirical evidences as
   to demonstrate how different rank aggregation methods affect the
   retrieval quality. (C) 2011 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Li, L (Reprint Author), Wuhan Univ Technol, Sch Comp Sci \& Technol, Wuhan, Peoples R China.
   Li, Lin, Wuhan Univ Technol, Sch Comp Sci \& Technol, Wuhan, Peoples R China.
   Xu, Guandong; Zhang, Yanchun, Victoria Univ, Sch Engn \& Sci, Melbourne, Vic 8001, Australia.
   Kitsuregawa, Masaru, Univ Tokyo, Inst Ind Sci, Tokyo 1138654, Japan.}},
DOI = {{10.1016/j.knosys.2011.04.001}},
ISSN = {{0950-7051}},
Keywords = {{Random walk; Rank aggregation; Query suggestion; Web search; Pairwise
   contest; Pairwise majority contest}},
Keywords-Plus = {{QUERY EXPANSION; USER LOGS}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{cathylilin@whut.edu.cn
   guandong.xu@vu.edu.au
   Yanchun.zhang@vu.edu.au
   kitsure@tkl.iis.u-tokyo.ac.jp}},
Cited-References = {{Grootjen FA, 2006, DATA KNOWL ENG, V56, P174, DOI 10.1016/j.datak.2005.03.006.
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Number-of-Cited-References = {{33}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{11}},
Journal-ISO = {{Knowledge-Based Syst.}},
Doc-Delivery-Number = {{804WA}},
Unique-ID = {{ISI:000293683500002}},
}

@article{ ISI:000295237400121,
Author = {Kukol, Andreas},
Title = {{Consensus virtual screening approaches to predict protein ligands}},
Journal = {{EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY}},
Year = {{2011}},
Volume = {{46}},
Number = {{9}},
Pages = {{4661-4664}},
Month = {{SEP}},
Abstract = {{In order to exploit the advantages of receptor-based virtual screening,
   namely time/cost saving and specificity, it is important to rely on
   algorithms that predict a high number of active ligands at the top ranks
   of a small molecule database. Towards that goal consensus methods
   combining the results of several docking algorithms were developed and
   compared against the individual algorithms. Furthermore, a recently
   proposed rescoring method based on drug efficiency indices was
   evaluated. Among AutoDock Vina 1.0, AutoDock 4.2 and GemDock, AutoDock
   Vina was the best performing single method in predicting high affinity
   ligands from a database of known ligands and decoys. The rescoring of
   predicted binding energies with the water/octanol partition coefficient
   did not lead to an improvement averaged over ten receptor targets.
   Various consensus algorithms were investigated and a simple combination
   of AutoDock and AutoDock Vina results gave the most consistent
   performance that showed early enrichment of known ligands for all
   receptor targets investigated. In case a number of ligands is known for
   a specific target, every method proposed in this study should be
   evaluated. (C) 2011 Elsevier Masson SAS. All rights reserved.}},
Publisher = {{ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER}},
Address = {{23 RUE LINOIS, 75724 PARIS, FRANCE}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Kukol, A (Reprint Author), Univ Hertfordshire, Sch Life Sci, Coll Lane, Hatfield AL10 9AB, Herts, England.
   Univ Hertfordshire, Sch Life Sci, Hatfield AL10 9AB, Herts, England.}},
DOI = {{10.1016/j.ejmech.2011.05.026}},
ISSN = {{0223-5234}},
Keywords = {{Molecular docking; In-silico screening; Consensus ranking; Benchmark;
   Comparison}},
Keywords-Plus = {{MOLECULAR DOCKING; INHIBITORS}},
Research-Areas = {{Pharmacology \& Pharmacy}},
Web-of-Science-Categories  = {{Chemistry, Medicinal}},
Author-Email = {{a.kukol@herts.ac.uk}},
Funding-Acknowledgement = {{School of Life Sciences at the Health and Human Sciences Research
   Institute, University of Hertfordshire, United Kingdom}},
Funding-Text = {{This work made use of the University of Hertfordshire Science and
   Technology Research Institute high-performance computing facility. The
   work was supported by the School of Life Sciences at the Health and
   Human Sciences Research Institute, University of Hertfordshire, United
   Kingdom.}},
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   Trott O, 2010, J COMPUT CHEM, V31, P455, DOI 10.1002/jcc.21334.}},
Number-of-Cited-References = {{15}},
Times-Cited = {{11}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{19}},
Journal-ISO = {{Eur. J. Med. Chem.}},
Doc-Delivery-Number = {{824YF}},
Unique-ID = {{ISI:000295237400121}},
}

@article{ ISI:000293775400011,
Author = {Joshi, L. and Shanmuganathan, V. A. and Kneebone, R. L. and Amoaku, W.},
Title = {{Performance in the Duke-Elder ophthalmology undergraduate prize
   examination and future careers in ophthalmology}},
Journal = {{EYE}},
Year = {{2011}},
Volume = {{25}},
Number = {{8}},
Pages = {{1027-1033}},
Month = {{AUG}},
Abstract = {{Aims Cognitive factors (eg, academic achievement) have had a significant
   role in selecting postgraduate surgical trainees in the past. This
   project sought to determine the role of a national undergraduate
   ophthalmology prize examination (Duke-Elder examination) in the
   selection of postgraduate ophthalmology trainees. This would also serve
   as a quality assurance exercise for the assessment, in which the
   ultimate aim is to encourage trainees into ophthalmology.
   Methods A retrospective analysis of the top 20 ranked candidates in the
   Duke-Elder examination from 1989 to 2005 (except 1995) was carried out
   to determine which of them subsequently entered the ophthalmic training
   and General Medical Council Specialist Registers.
   Results Out of the top 20 candidates in the exam, 29.5\% went into
   specialist training in ophthalmology. Some appeared in the top 20 more
   than once, with 56\% of them going into ophthalmic training, but they
   had a similar median time to enter training as those who appeared in the
   top 20 once. There was no significant evidence to suggest that the
   overall median ranking scores between the UK medical schools differed (P
   = 0.23; Kruskal-Wallis test). However, there was a marked difference in
   frequency of top 20 candidates from each medical school, which could not
   be explained by the size of the medical school alone.
   Conclusion It is difficult to conclude from these findings the
   importance that the Duke-Elder examination has in the selection of
   trainees into ophthalmology. The role of cognitive factors in selection
   into postgraduate medical/surgical training is discussed, along with the
   potential academic criteria, which may influence interview scores. Eye
   (2011) 25, 1027-1033; doi:10.1038/eye.2011.114; published online 13 May
   2011}},
Publisher = {{NATURE PUBLISHING GROUP}},
Address = {{MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Amoaku, W (Reprint Author), Queens Med Ctr, Div Ophthalmol \& Visual Sci, Eye \& ENT Ctr, B Floor, Nottingham NG7 2UH, England.
   Amoaku, W., Queens Med Ctr, Div Ophthalmol \& Visual Sci, Eye \& ENT Ctr, Nottingham NG7 2UH, England.
   Kneebone, R. L., Univ London Imperial Coll Sci Technol \& Med, Dept Surg \& Canc, London, England.
   Shanmuganathan, V. A., Moorfields Eye Hosp NHS Fdn, London, England.
   Joshi, L., Moorfields Eye Hosp, Dept Clin Ophthalmol, UCL Inst Ophthalmol, London, England.}},
DOI = {{10.1038/eye.2011.114}},
ISSN = {{0950-222X}},
Keywords = {{selection; postgraduate; ophthalmology; undergraduate}},
Keywords-Plus = {{TRAINING EXAMINATION SCORES; BIOMEDICAL KNOWLEDGE; CLINICAL-DIAGNOSIS;
   PROGRAM DIRECTORS; SELECT RESIDENTS; BASIC SCIENCE; ACCURACY; SURGERY;
   SPEED}},
Research-Areas = {{Ophthalmology}},
Web-of-Science-Categories  = {{Ophthalmology}},
Author-Email = {{wma@nottingham.ac.uk}},
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Number-of-Cited-References = {{36}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Eye}},
Doc-Delivery-Number = {{806BG}},
Unique-ID = {{ISI:000293775400011}},
}

@article{ ISI:000293035400016,
Author = {Zaretzki, Jed and Bergeron, Charles and Rydberg, Patrik and Huang,
   Tao-wei and Bennett, Kristin P. and Breneman, Curt M.},
Title = {{RS-Predictor: A New Tool for Predicting Sites of Cytochrome
   P450-Mediated Metabolism Applied to CYP 3A4}},
Journal = {{JOURNAL OF CHEMICAL INFORMATION AND MODELING}},
Year = {{2011}},
Volume = {{51}},
Number = {{7}},
Pages = {{1667-1689}},
Month = {{JUL}},
Abstract = {{This article describes RegioSelectivity-Predictor (RS-Predictor), a new
   in silico method for generating predictive models of P450-mediated
   metabolism for drug-like compounds. Within this method, potential sites
   of metabolism (SOMs) are represented as ``metabolophores{''}: A concept
   that describes the hierarchical combination of topological and quantum
   chemical descriptors needed to represent the reactivity of potential
   metabolic reaction sites. RS-Predictor modeling involves the use of
   metabolophore descriptors together with multiple-instance ranking
   (MERank) to generate an optimized descriptor weight vector that encodes
   regioselectivity trends across all cases in a training set. The
   resulting pathway-independent (O-dealkylation vs N-oxidation vs Csp(3)
   hydroxylation, etc.), isozyme-specific regioselectivity model may be
   used to predict potential metabolic liabilities. In the present work,
   cross-validated RS-Predictor models were generated for a set of 394
   substrates of CYP 3A4 as a proof-of-principle for the method. Rank
   aggregation was then employed to merge independently generated
   predictions for each substrate into a single consensus prediction. The
   resulting consensus RS-Predictor models were shown to reliably identify
   at least one observed site of metabolism in the top two rank-positions
   on 78\% of the substrates. Comparisons between RS-Predictor and
   previously described regioselectivity prediction methods reveal new
   insights into how in silico metabolite prediction methods should be
   compared.}},
Publisher = {{AMER CHEMICAL SOC}},
Address = {{1155 16TH ST, NW, WASHINGTON, DC 20036 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Breneman, CM (Reprint Author), Rensselaer Polytech Inst, Dept Chem \& Chem Biol, Troy, NY 12180 USA.
   Zaretzki, Jed; Huang, Tao-wei; Breneman, Curt M., Rensselaer Polytech Inst, Dept Chem \& Chem Biol, Troy, NY 12180 USA.
   Bergeron, Charles; Bennett, Kristin P., Rensselaer Polytech Inst, Dept Math Sci, Troy, NY 12180 USA.
   Rydberg, Patrik, Univ Copenhagen, DK-2100 Copenhagen, Denmark.}},
DOI = {{10.1021/ci2000488}},
ISSN = {{1549-9596}},
Keywords-Plus = {{DRUG-METABOLISM; IN-SILICO; P450; MODELS; INHIBITORS; ENZYMES; 2C9; 2D6;
   REGIOSELECTIVITY; DOCKING}},
Research-Areas = {{Pharmacology \& Pharmacy; Chemistry; Computer Science}},
Web-of-Science-Categories  = {{Chemistry, Medicinal; Chemistry, Multidisciplinary; Computer Science,
   Information Systems; Computer Science, Interdisciplinary Applications}},
Author-Email = {{brenec@rpi.edu}},
ResearcherID-Numbers = {{Rydberg, Patrik/A-7450-2008}},
ORCID-Numbers = {{Rydberg, Patrik/0000-0001-6108-9246}},
Funding-Acknowledgement = {{NIH {[}1P20HG003899-01, R01LM009731]; ONR {[}N00014-06-1-0014]; Alfred
   Benzon foundation; Danish Medical Research Council}},
Funding-Text = {{The authors like to thank NIH grants (1P20HG003899-01) and
   (R01LM009731), ONR grant (N00014-06-1-0014) the Alfred Benzon foundation
   and the Danish Medical Research Council for funding. We also thank the
   RPI Center for Biotechnology and Interdisciplinary Studies for being an
   excellent collaborative work environment. We would also like express our
   gratitude to Optibrium for providing access to StarDrop and permission
   to publish results, Dr. Gregory Moore for contributions to the MIRank
   subgradient algorithm, and Michael Krein for systems support; MOE,
   Molecular Operating Environment.}},
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   METASITE USER MANUAL.}},
Number-of-Cited-References = {{47}},
Times-Cited = {{32}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{11}},
Journal-ISO = {{J. Chem Inf. Model.}},
Doc-Delivery-Number = {{796EU}},
Unique-ID = {{ISI:000293035400016}},
}

@article{ ISI:000288580800015,
Author = {Betzler, Nadja and Guo, Jiong and Komusiewicz, Christian and
   Niedermeier, Rolf},
Title = {{Average parameterization and partial kernelization for computing medians}},
Journal = {{JOURNAL OF COMPUTER AND SYSTEM SCIENCES}},
Year = {{2011}},
Volume = {{77}},
Number = {{4, SI}},
Pages = {{774-789}},
Month = {{JUL}},
Abstract = {{We propose an effective polynomial-time preprocessing strategy for
   intractable median problems. Developing a new methodological framework,
   we show that if the input objects of generally intractable problems
   exhibit a sufficiently high degree of similarity between each other on
   average, then there are efficient exact solving algorithms. In other
   words, we show that the median problems SWAP MEDIAN PERMUTATION,
   CONSENSUS CLUSTERING, KEMENY SCORE, and KEMENY TIE SCORE all are
   fixed-parameter tractable with respect to the parameter ``average
   distance between input objects{''}. To this end, we develop the novel
   concept of ``partial kernelization{''} and, furthermore, identify
   polynomial-time solvable special cases for the considered problems. (C)
   2010 Elsevier Inc. All rights reserved.}},
Publisher = {{ACADEMIC PRESS INC ELSEVIER SCIENCE}},
Address = {{525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Komusiewicz, C (Reprint Author), Univ Jena, Inst Informat, Ernst Abbe Pl 2, D-07743 Jena, Germany.
   Betzler, Nadja; Komusiewicz, Christian; Niedermeier, Rolf, Univ Jena, Inst Informat, D-07743 Jena, Germany.
   Guo, Jiong, Univ Saarland, D-66123 Saarbrucken, Germany.}},
DOI = {{10.1016/j.jcss.2010.07.005}},
ISSN = {{0022-0000}},
Keywords = {{Polynomial-time preprocessing; Data reduction; Fixed-parameter
   tractability; Rank aggregation; Consensus clustering}},
Keywords-Plus = {{ALGORITHMS}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Hardware \& Architecture; Computer Science, Theory \&
   Methods}},
Author-Email = {{nadja.betzler@uni-jena.de
   jguo@mmci.uni-saarland.de
   c.komus@uni-jena.de
   rolf.niedermeier@uni-jena.de}},
ORCID-Numbers = {{Komusiewicz, Christian/0000-0003-0829-7032}},
Funding-Acknowledgement = {{DFG {[}NI 369/10, NI 369/7]; Carl-Zeiss-Stiftung}},
Funding-Text = {{Supported by the DFG, project PAWS, NI 369/10.; Supported by a PhD
   fellowship of the Carl-Zeiss-Stiftung and the DFG, project PABI, NI
   369/7.}},
Cited-References = {{Ailon N, 2008, J ACM, V55, DOI 10.1145/1411509.1411513.
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Number-of-Cited-References = {{32}},
Times-Cited = {{9}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{J. Comput. Syst. Sci.}},
Doc-Delivery-Number = {{737PN}},
Unique-ID = {{ISI:000288580800015}},
}

@article{ ISI:000288371400009,
Author = {Jiang, Xiaoye and Lim, Lek-Heng and Yao, Yuan and Ye, Yinyu},
Title = {{Statistical ranking and combinatorial Hodge theory}},
Journal = {{MATHEMATICAL PROGRAMMING}},
Year = {{2011}},
Volume = {{127}},
Number = {{1, SI}},
Pages = {{203-244}},
Month = {{MAR}},
Abstract = {{We propose a technique that we call HodgeRank for ranking data that may
   be incomplete and imbalanced, characteristics common in modern datasets
   coming from e-commerce and internet applications. We are primarily
   interested in cardinal data based on scores or ratings though our
   methods also give specific insights on ordinal data. From raw ranking
   data, we construct pairwise rankings, represented as edge flows on an
   appropriate graph. Our statistical ranking method exploits the graph
   Helmholtzian, which is the graph theoretic analogue of the Helmholtz
   operator or vector Laplacian, in much the same way the graph Laplacian
   is an analogue of the Laplace operator or scalar Laplacian. We shall
   study the graph Helmholtzian using combinatorial Hodge theory, which
   provides a way to unravel ranking information from edge flows. In
   particular, we show that every edge flow representing pairwise ranking
   can be resolved into two orthogonal components, a gradient flow that
   represents the l(2)-optimal global ranking and a divergence-free flow
   (cyclic) that measures the validity of the global ranking obtained-if
   this is large, then it indicates that the data does not have a good
   global ranking. This divergence-free flow can be further decomposed
   orthogonally into a curl flow (locally cyclic) and a harmonic flow
   (locally acyclic but globally cyclic); these provides information on
   whether inconsistency in the ranking data arises locally or globally.
   When applied to statistical ranking problems, Hodge decomposition sheds
   light on whether a given dataset may be globally ranked in a meaningful
   way or if the data is inherently inconsistent and thus could not have
   any reasonable global ranking; in the latter case it provides
   information on the nature of the inconsistencies. An obvious advantage
   over the NP-hardness of Kemeny optimization is that HodgeRank may be
   easily computed via a linear least squares regression. We also discuss
   connections with well-known ordinal ranking techniques such as Kemeny
   optimization and Borda count from social choice theory.}},
Publisher = {{SPRINGER}},
Address = {{233 SPRING ST, NEW YORK, NY 10013 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Lim, LH (Reprint Author), Univ Calif Berkeley, Dept Math, Berkeley, CA 94720 USA.
   Lim, Lek-Heng, Univ Calif Berkeley, Dept Math, Berkeley, CA 94720 USA.
   Jiang, Xiaoye, Stanford Univ, Inst Computat \& Math Engn, Stanford, CA 94305 USA.
   Yao, Yuan, Peking Univ, Sch Math Sci, LMAM, Beijing 100871, Peoples R China.
   Yao, Yuan, Peking Univ, Key Lab Machine Percept MOE, Beijing 100871, Peoples R China.
   Ye, Yinyu, Stanford Univ, Dept Management Sci \& Engn, Stanford, CA 94305 USA.}},
DOI = {{10.1007/s10107-010-0419-x}},
ISSN = {{0025-5610}},
Keywords = {{Statistical ranking; Rank aggregation; Combinatorial Hodge theory;
   Discrete exterior calculus; Combinatorial Laplacian; Hodge Laplacian;
   Graph Helmholtzian; HodgeRank; Kemeny optimization; Borda count}},
Keywords-Plus = {{EQUAL STANDARD DEVIATIONS; PAIRED COMPARISONS; LEAST-SQUARES; ALGORITHM}},
Research-Areas = {{Computer Science; Operations Research \& Management Science; Mathematics}},
Web-of-Science-Categories  = {{Computer Science, Software Engineering; Operations Research \&
   Management Science; Mathematics, Applied}},
Author-Email = {{xiaoyej@stanford.edu
   lekheng@galton.uchicago.edu
   yuany@math.pku.edu.cn
   yinyu-ye@stanford.edu}},
Funding-Acknowledgement = {{ARO {[}W911NF-04-R-0005 BAA]; School of Engineering fellowship at
   Stanford; Gerald J. Liebermann fellowship at Stanford; National Basic
   Research Program of China (973 Program) {[}2011CB809105]; NSFC
   {[}61071157]; Microsoft Research Asia; DARPA {[}HR0011-05-1-0007]; NSF
   {[}DMS 0354543]; Peking University; AFOSR {[}FA9550-09-1-0306]; DOE
   {[}DE-SC0002009]}},
Funding-Text = {{X. Jiang acknowledges support from ARO Grant W911NF-04-R-0005 BAA and
   the School of Engineering fellowship at Stanford. L.-H. Lim acknowledges
   support from the Gerald J. Liebermann fellowship at Stanford and the
   Charles B. Morrey assistant professorship at Berkeley.; Y. Yao
   acknowledges supports from the National Basic Research Program of China
   (973 Program 2011CB809105), NSFC (61071157), Microsoft Research Asia,
   DARPA Grant HR0011-05-1-0007, NSF Grant DMS 0354543, and a professorship
   in the Hundred Talents Program at Peking University. Y. Ye acknowledges
   support from AFOSR Grant FA9550-09-1-0306 and DOE Grant DE-SC0002009.}},
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Number-of-Cited-References = {{46}},
Times-Cited = {{21}},
Usage-Count-(Last-180-days) = {{9}},
Usage-Count-Since-2013 = {{16}},
Journal-ISO = {{Math. Program.}},
Doc-Delivery-Number = {{734WI}},
Unique-ID = {{ISI:000288371400009}},
}

@article{ ISI:000286118400004,
Author = {Spain, Merrielle and Perona, Pietro},
Title = {{Measuring and Predicting Object Importance}},
Journal = {{INTERNATIONAL JOURNAL OF COMPUTER VISION}},
Year = {{2011}},
Volume = {{91}},
Number = {{1}},
Pages = {{59-76}},
Month = {{JAN}},
Abstract = {{How important is a particular object in a photograph of a complex scene?
   We propose a definition of importance and present two methods for
   measuring object importance from human observers. Using this ground
   truth, we fit a function for predicting the importance of each object
   directly from a segmented image; our function combines a large number of
   object-related and image-related features. We validate our importance
   predictions on 2,841 objects and find that the most important objects
   may be identified automatically. We find that object position and size
   are particularly informative, while a popular measure of saliency is
   not.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Spain, M (Reprint Author), 1200 E Calif Blvd,MC 136-93, Pasadena, CA 91125 USA.}},
DOI = {{10.1007/s11263-010-0376-0}},
ISSN = {{0920-5691}},
Keywords = {{Visual recognition; Object recognition; Importance; Perception;
   Keywording; Saliency; Rank aggregation; Amazon Mechanical Turk}},
Keywords-Plus = {{IMAGE FEATURES; ATTENTION; SELECTION; MODEL}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{spain@caltech.edu}},
Funding-Acknowledgement = {{National Science Foundation; Office of Naval Research
   {[}N00014-06-1-0734]; National Institutes of Health {[}R01 DA022777]}},
Funding-Text = {{This material is based upon work supported under a National Science
   Foundation Graduate Research Fellowship, Office of Naval Research grant
   N00014-06-1-0734, and National Institutes of Health grant R01 DA022777.}},
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   Sorokin A., 2008, CVPR.
   SPAIN M, 2008, P EUR C COMP VIS ECC.
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   von Ahn L., 2004, CHI 04, P319, DOI DOI 10.1145/985692.985733.
   Zhang H, 2006, CVPR, P2126.}},
Number-of-Cited-References = {{35}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{Int. J. Comput. Vis.}},
Doc-Delivery-Number = {{705HB}},
Unique-ID = {{ISI:000286118400004}},
}

@article{ ISI:000285442400014,
Author = {Akritidis, Leonidas and Katsaros, Dimitrios and Bozanis, Panayiotis},
Title = {{Effective rank aggregation for metasearching}},
Journal = {{JOURNAL OF SYSTEMS AND SOFTWARE}},
Year = {{2011}},
Volume = {{84}},
Number = {{1, SI}},
Pages = {{130-143}},
Month = {{JAN}},
Note = {{23rd International Conference on Advanced Information Networking and
   Applications Workshops, Bradford, ENGLAND, MAY 26-29, 2009}},
Organization = {{IEEE}},
Abstract = {{Nowadays, mashup services and especially metasearch engines play an
   increasingly important role on the Web. Most of users use them directly
   or indirectly to access and aggregate information from more than one
   data sources. Similarly to the rest of the search systems, the
   effectiveness of a metasearch engine is mainly determined by the quality
   of the results it returns in response to user queries. Since these
   services do not maintain their own document index, they exploit multiple
   search engines using a rank aggregation method in order to classify the
   collected results. However, the rank aggregation methods which have been
   proposed until now, utilize a very limited set of parameters regarding
   these results, such as the total number of the exploited resources and
   the rankings they receive from each individual resource. In this paper
   we present QuadRank, a new rank aggregation method, which takes into
   consideration additional information regarding the query terms, the
   collected results and the data correlated to each of these results
   (title, textual snippet. URL, individual ranking and others). We have
   implemented and tested QuadRank in a real-world metasearch engine.
   QuadSearch, a system developed as a testbed for algorithms related to
   the wide problem of metasearching. The name QuadSearch is related to the
   current number of the exploited engines (four). We have exhaustively
   tested QuadRank for both effectiveness and efficiency in the real-world
   search environment of QuadSearch and also, using a task from the recent
   TREC-2009 conference. The results we present in our experiments reveal
   that in most cases QuadRank outperformed all component engines, another
   metasearch engine (Dogpile) and two successful rank aggregation methods,
   Borda Count and the Outranking Approach. (C) 2010 Elsevier Inc. All
   rights reserved.}},
Publisher = {{ELSEVIER SCIENCE INC}},
Address = {{360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Katsaros, D (Reprint Author), Univ Thessaly, Dept Comp \& Commun Engn, Glavani 37, Volos 38221, Greece.
   Akritidis, Leonidas; Katsaros, Dimitrios; Bozanis, Panayiotis, Univ Thessaly, Dept Comp \& Commun Engn, Volos 38221, Greece.}},
DOI = {{10.1016/j.jss.2010.09.001}},
ISSN = {{0164-1212}},
Keywords = {{Ranking; Rank aggregation; Rank fusion; Metasearch; Borda Count; Search
   engines; Information search; Information retrieval; Web}},
Keywords-Plus = {{ENGINES; WEB}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Software Engineering; Computer Science, Theory \&
   Methods}},
Author-Email = {{dkatsar@inf.uth.gr}},
Cited-References = {{AILON N., 2005, P 37 ANN ACM S THEOR, P684, DOI 10.1145/1060590.1060692.
   ALLEN J, 2009, CSE8337 SO METH U.
   Beg MMS, 2003, WORLD WIDE WEB, V6, P5, DOI 10.1023/A:1022344031752.
   Lu W, 2006, LECT NOTES COMPUT SC, V3977, P161.
   Ailon N, 2007, PROCEEDINGS OF THE EIGHTEENTH ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS, P415.
   Coppersmith D, 2006, PROCEEDINGS OF THE SEVENTHEENTH ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS, P776, DOI 10.1145/1109557.1109642.
   YOUNG HP, 1978, SIAM J APPL MATH, V35, P285, DOI 10.1137/0135023.
   Meng WY, 2002, ACM COMPUT SURV, V34, P48, DOI 10.1145/505282.505284.
   Aslam J. A., 2001, P 24 ANN INT ACM SIG, P276, DOI DOI 10.1145/383952.384007.
   ASLAM JA, 2001, P ACM INT C RES DEV, P386.
   DECONDE R. P., 2006, STAT APPL GENET MOL, V5, P1.
   Dwork C, 2001, P 10 INT C WORLD WID, P613, DOI DOI 10.1145/371920.372165.
   Fagin R, 2003, P 2003 ACM SIGMOD IN, P301, DOI DOI 10.1145/872757.872795.
   FARAH M, 2007, P ACM INT C RES DEV.
   Liu Y. T., 2007, P 16 INT C WORLD WID, P481, DOI 10.1145/1242572.1242638.
   Manning C. D., 2008, INTRO INFORM RETRIEV.
   Oztekin B., 2002, P 11 INT WORLD WID W, P333.
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   SAARI DG, 2000, ECONOMIST       0304, P83.
   SCULLEY D, 2007, P SIAM C DAT MIN SDM.
   Shokouhi M, 2007, LECT NOTES COMPUT SC, V4425, P185.
   Soboroff I., 2009, OVERVIEW TREC 2009 W.
   SOULDATOS S, 2005, P ICML WORKSH LEARN.
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   Vogt C. C., 1999, THESIS U CALIFORNIA.
   Vogt C. C., 1999, Information Retrieval, V1, DOI 10.1023/A:1009980820262.}},
Number-of-Cited-References = {{28}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{J. Syst. Softw.}},
Doc-Delivery-Number = {{696LH}},
Unique-ID = {{ISI:000285442400014}},
}

@article{ ISI:000296910400022,
Author = {Sen Gupta, T. K. and Hays, R. B. and Kelly, G. and Buettner, P. G.},
Title = {{Are medical student results affected by allocation to different sites in
   a dispersed rural medical school?}},
Journal = {{RURAL AND REMOTE HEALTH}},
Year = {{2011}},
Volume = {{11}},
Number = {{1}},
Month = {{JAN-MAR}},
Abstract = {{Introduction: As medical education becomes more decentralised, and
   greater use is made of rural clinical schools and other dispersed sites,
   attention is being paid to the quality of the learning experiences
   across these sites. This article explores this issue by analysing the
   performance data of 4 cohorts of students in a dispersed clinical school
   model across 4 sites. The study is set in a newly established medical
   school in a regional area with a model of dispersed education, using
   data from the second to fifth cohorts to graduate from this school.
   Methods: Summative assessment results of 4 graduating cohorts were
   examined over the final 2 years of the course. Two analyses were
   conducted: an analysis of variance of mean scores in both years across
   the 4 sites; and an analysis of the effect of moving to different
   clinical schools on the students' rank order of performance by use of
   the Kruskal-Wallis test.
   swResults: Analysis revealed no significant difference in the mean
   scores of the students studying at each site, and no significant
   differences overall in the median ranking across the years. Some small
   changes in the relative ranking of students were noticed, and
   workplace-based assessment scores in the final year were higher than the
   examination-based scores in the previous year.
   Conclusions: The choice of clinical school site for the final 2 years of
   an undergraduate rural medical school appears to have no effect on mean
   assessment scores and only a minor effect on the rank order of student
   scores. Workplace-based assessment produces higher scores but also has
   little effect on student rank order. Further studies are necessary to
   replicate these findings in other settings and demonstrate that student
   learning experiences in rural sites, while popular with students,
   translate into required learning outcomes, as measured by summative
   assessments.}},
Publisher = {{AUSTRALIAN RURAL HEALTH EDUC NETWORK}},
Address = {{PO BOX 242, DEAKIN WEST, ACT 2600, AUSTRALIA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Sen Gupta, TK (Reprint Author), James Cook Univ, Sch Med \& Dent, Townsville, Qld, Australia.
   Sen Gupta, T. K.; Kelly, G., James Cook Univ, Sch Med \& Dent, Townsville, Qld, Australia.
   Hays, R. B., Bond Univ, Fac Hlth Sci \& Med, Southport, Qld 4229, Australia.
   Buettner, P. G., Sch Publ Hlth Trop Med \& Rehabil Sci, Townsville, Qld, Australia.}},
Article-Number = {{1511}},
ISSN = {{1445-6354}},
Keywords = {{assessment; clinical teaching; medical education; rural clinical school;
   undergraduate}},
Keywords-Plus = {{PERFORMANCE; EXPERIENCE}},
Research-Areas = {{Public, Environmental \& Occupational Health}},
Web-of-Science-Categories  = {{Public, Environmental \& Occupational Health}},
Cited-References = {{Dornan T, 2007, MED EDUC, V41, P84, DOI 10.1111/j.1365-2929.2006.02652.x.
   Worley P, 2004, BRIT MED J, V328, P207, DOI 10.1136/bmj.328.7433.207.
   {*}AUSTR MED COUNC, 2009, ASS ACCR MED SCH S 3.
   Bianchi F, 2008, MED TEACH, V30, P67, DOI 10.1080/01421590701754144.
   Colquhoun C, 2009, MED TEACH, V31, P1084.
   Hays R, 2001, Aust J Rural Health, V9 Suppl 1, pS2.
   PATRICK CJ, WIL WORKBASE IMMERSE.
   Tesson G, 2005, Rural Remote Health, V5, P397.}},
Number-of-Cited-References = {{8}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{Rural Remote Health}},
Doc-Delivery-Number = {{846NL}},
Unique-ID = {{ISI:000296910400022}},
}

@article{ ISI:000286954000009,
Author = {Leszczynski, Krzysztof},
Title = {{Different Evaluations of Motor-Manual Wood Harvesting Processes on the
   Basis of Conjoint Analysis}},
Journal = {{CROATIAN JOURNAL OF FOREST ENGINEERING}},
Year = {{2010}},
Volume = {{31}},
Number = {{2}},
Pages = {{165-172}},
Month = {{DEC}},
Abstract = {{The aim of this paper was the conjoint analysis of wood harvesting
   processes performed using motor-manual methods. Distribution of the
   characteristics consisted of nine features, based on the results of
   multidimensional scaling, which were aggregated into two groups:
   ergonomic (5) and technological (4). The scope of research was limited
   to four wood harvesting processes. The cuts were carried out in selected
   100-year old spruce stands on the steep terrain (13-30 degrees) in the
   Beskid Zywiecki Mts. The value of utility function was defined on the
   basis of normalized eigenvectors for the comparison matrix. The weight
   of the features was defined on the basis of the Tytyk (2001) simplified
   method of rank aggregation by preserving the maximum values (for
   ergonomic issues), the Satty method of subjective assessment and the
   partially determined stochastic factors (for technological issues). The
   results of the calculations indicate the occurrence of dominant
   preferences within two groups of factors and their mutual polarization.
   The results of the total evaluation indicate disappearance of the strong
   dominance of alternatives.}},
Publisher = {{CROATION FORESTS}},
Address = {{FORESTRY FACULTY ZAGREB UNIV, PO BOX 422, ZAGREB, HR-10 002, CROATIA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Leszczynski, K (Reprint Author), Univ Agr Krakow, Fac Forestry, Dept Forest \& Wood Utilizat, Al 29 Listopada 46, PL-31425 Krakow, Poland.
   Univ Agr Krakow, Fac Forestry, Dept Forest \& Wood Utilizat, PL-31425 Krakow, Poland.}},
ISSN = {{1845-5719}},
Keywords = {{Conjoint Analysis; ergonomics; forestry; wood utilization}},
Research-Areas = {{Forestry}},
Web-of-Science-Categories  = {{Forestry}},
Author-Email = {{rlleszcz@cyf-kr.edu.pl}},
Cited-References = {{KARHU O, 1977, APPL ERGON, V8, P199, DOI 10.1016/0003-6870(77)90164-8.
   BODELSCHWINGH E, 2005, HOLZ ZENTRALBLATT, V86, P1163.
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   HEINIMANN RH, 2007, SCHWEIZERISCHE Z FOR, V158, P235.
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   STAMPFER K, 1996, DETERMINING WORK LOA.
   Tytyk E., 2001, PROJEKTOWANIE ERGONO.}},
Number-of-Cited-References = {{18}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Croat. J. For. Eng.}},
Doc-Delivery-Number = {{716FH}},
Unique-ID = {{ISI:000286954000009}},
}

@article{ ISI:000283583500028,
Author = {Kiefer, Christopher S. and Colletti, James E. and Bellolio, M. Fernanda
   and Hess, Erik P. and Woolridge, Dale P. and Thomas, Kristen B. and
   Sadosty, Annie T.},
Title = {{The ``Good{''} Dean's Letter}},
Journal = {{ACADEMIC MEDICINE}},
Year = {{2010}},
Volume = {{85}},
Number = {{11}},
Pages = {{1705-1708}},
Month = {{NOV}},
Abstract = {{Purpose
   To determine whether a correlation exists between the term ``good{''} on
   the summative, comparative assessment of a student's Medical Student
   Performance Evaluation (MSPE) and his or her actual performance in
   medical school.
   Method
   The authors reviewed the MSPEs submitted to three residency programs to
   determine the presence of the term ``good{''} in either the summary
   paragraph or the appendices. Next, they noted, for institutions using
   ``good,{''} the percentile rankings of those students who received
   ``good{''} as a descriptor. To examine the consistency among
   institutions regarding the percentile ranking denoted by ``good,{''}
   they dichotomized the data into students below and above the bottom 25th
   percentile. They analyzed the data using a nonparametric test because of
   their nonnormal distribution.
   Results
   The authors collected MSPEs from 122 of the 125 Liaison Committee on
   Medical Education-accredited medical schools that were graduating
   students in 2008. Of these 122 institutions, 34 (28\%) used the term
   ``good.{''} All 34 institutions used the term to characterize students
   in the bottom 50\% of the graduating class. The authors found a
   significant difference in the percentile ranking of students described
   as ``good{''} between institutions using it to describe the bottom 25\%
   and institutions using the term to describe those in the 25th to 50th
   percentiles (median ranking of 12.5\% versus 30\%, P < .0001).
   Conclusions
   Overall, the term ``good{''} in the MSPE describes students in the
   bottom 50\% of the class; therefore, the term ``good,{''} as used to
   describe performance in medical school, consistently indicates
   below-average performance.}},
Publisher = {{LIPPINCOTT WILLIAMS \& WILKINS}},
Address = {{530 WALNUT ST, PHILADELPHIA, PA 19106-3621 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Colletti, JE (Reprint Author), 200 1st St SW, Rochester, MN 55905 USA.
   Kiefer, Christopher S.; Colletti, James E.; Bellolio, M. Fernanda; Hess, Erik P., Mayo Clin, Dept Emergency Med, Rochester, MN USA.
   Woolridge, Dale P., Univ Arizona, Tucson, AZ USA.
   Thomas, Kristen B., Mayo Clin, Dept Radiol, Rochester, MN USA.}},
DOI = {{10.1097/ACM.0b013e3181f55a10}},
ISSN = {{1040-2446}},
Keywords-Plus = {{EMERGENCY-MEDICINE RESEARCH; PROGRAM DIRECTORS; PERFORMANCE; SELECTION;
   IMPROVEMENT}},
Research-Areas = {{Education \& Educational Research; Health Care Sciences \& Services}},
Web-of-Science-Categories  = {{Education, Scientific Disciplines; Health Care Sciences \& Services}},
Author-Email = {{Colletti.james@mayo.edu}},
ORCID-Numbers = {{Bellolio, M. Fernanda/0000-0002-1632-4750}},
Cited-References = {{Worster A, 2004, ACAD EMERG MED, V11, P187, DOI 10.1197/j.aem.2003.03.002.
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   Lee AG, 2008, SURV OPHTHALMOL, V53, P164, DOI {[}10.1016/j.survophthal.2007.12.007, 10.1016/.i.survophthal.2007.12.007].
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   1993, MERRIAM WEBSTERS COL, P502.}},
Number-of-Cited-References = {{17}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{9}},
Journal-ISO = {{Acad. Med.}},
Doc-Delivery-Number = {{672LC}},
Unique-ID = {{ISI:000283583500028}},
}

@article{ ISI:000284350300004,
Author = {Shao, Li and Wu, Leihong and Fan, Xiaohui and Cheng, Yiyu},
Title = {{Consensus Ranking Approach to Understanding the Underlying Mechanism
   With QSAR}},
Journal = {{JOURNAL OF CHEMICAL INFORMATION AND MODELING}},
Year = {{2010}},
Volume = {{50}},
Number = {{11}},
Pages = {{1941-1948}},
Month = {{NOV}},
Abstract = {{Constructing a highly predictive model and exploiting the underlying
   mechanism associated with a specific property of chemicals are the two
   main goals of quantitative structure-activity relationship analysis
   (QSAR). However, the latter has long been carried out as a byproduct of
   model construction. Here we confirmed for the first time in this study
   that conventional descriptor selection methods designed to develop a
   best predictive model are likely not suitable for mechanistic analysis,
   i.e., the selected descriptors strongly depended on the selection of
   chemicals in the training sets. As an alternative, a consensus ranking
   protocol was proposed to select a robust descriptor set for mechanistic
   analysis, which can successfully overcome the above shortcoming.
   Moreover, the consistently inferior model performance using descriptors
   selected for mechanistic analysis suggested the irreplaceable role of
   model development in achieving models with the best predictive
   capability.}},
Publisher = {{AMER CHEMICAL SOC}},
Address = {{1155 16TH ST, NW, WASHINGTON, DC 20036 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Fan, XH (Reprint Author), Zhejiang Univ, Coll Pharmaceut Sci, Pharmaceut Informat Inst, Hangzhou 310058, Zhejiang, Peoples R China.
   Shao, Li; Wu, Leihong; Fan, Xiaohui; Cheng, Yiyu, Zhejiang Univ, Coll Pharmaceut Sci, Pharmaceut Informat Inst, Hangzhou 310058, Zhejiang, Peoples R China.}},
DOI = {{10.1021/ci100305g}},
ISSN = {{1549-9596}},
Keywords-Plus = {{PROTEIN-TYROSINE KINASES; PYRROLOTRIAZINE DUAL INHIBITORS; ENHANCED
   REPLACEMENT METHOD; HIV INTEGRASE INHIBITORS; QUANTITATIVE STRUCTURE;
   TETRAHYMENA-PYRIFORMIS; MOLECULAR DESCRIPTORS; PHYSICAL-PROPERTIES;
   QSPR; EGFR}},
Research-Areas = {{Pharmacology \& Pharmacy; Chemistry; Computer Science}},
Web-of-Science-Categories  = {{Chemistry, Medicinal; Chemistry, Multidisciplinary; Computer Science,
   Information Systems; Computer Science, Interdisciplinary Applications}},
Author-Email = {{fanxh@zju.edu.cn
   chengyy@zju.edu.cn}},
ORCID-Numbers = {{Wu, Leihong/0000-0002-4093-3708}},
Funding-Acknowledgement = {{National Science Foundation of China {[}30801556]; Zhejiang Province
   Science and Technology Plan Project {[}2008C23065, R2080693]; Research
   Fund for the Doctoral Program of Higher Education of China
   {[}20090101110126]}},
Funding-Text = {{This work was supported by the National Science Foundation of China (no.
   30801556), the Zhejiang Province Science and Technology Plan Project
   (no. 2008C23065 and R2080693), and the Research Fund for the Doctoral
   Program of Higher Education of China (no. 20090101110126).}},
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Number-of-Cited-References = {{32}},
Times-Cited = {{15}},
Usage-Count-(Last-180-days) = {{8}},
Usage-Count-Since-2013 = {{16}},
Journal-ISO = {{J. Chem Inf. Model.}},
Doc-Delivery-Number = {{681VU}},
Unique-ID = {{ISI:000284350300004}},
}

@article{ ISI:000286342700012,
Author = {Sen Gupta, T. K. and Hays, R. B. and Kelly, G. and Buettner, P. G.},
Title = {{Are medical student results affected by allocation to different sites in
   a dispersed rural medical school?}},
Journal = {{RURAL AND REMOTE HEALTH}},
Year = {{2010}},
Volume = {{10}},
Number = {{4}},
Month = {{OCT-DEC}},
Abstract = {{Introduction: As medical education becomes more decentralised, and
   greater use is made of rural clinical schools and other dispersed sites,
   attention is being paid to the quality of the learning experiences
   across these sites. This article explores this issue by analysing the
   performance data of 4 cohorts of students in a dispersed clinical school
   model across 4 sites. The study is set in a newly established medical
   school in a regional area with a model of dispersed education, using
   data from the second to fifth cohorts to graduate from this school.
   Methods: Summative assessment results of 4 graduating cohorts were
   examined over the final 2 years of the course. Two analyses were
   conducted: an analysis of variance of mean scores in both years across
   the 4 sites; and an analysis of the effect of moving to different
   clinical schools on the students' rank order of performance by use of
   the Kruskal-Wallis test.
   Results: Analysis revealed no significant difference in the mean scores
   of the students studying at each site, and no significant differences
   overall in the median ranking across the years. Some small changes in
   the relative ranking of students were noticed, and workplace-based
   assessment scores in the final year were higher than the
   examination-based scores in the previous year.
   Conclusions: The choice of clinical school site for the final 2 years of
   an undergraduate rural medical school appears to have no effect on mean
   assessment scores and only a minor effect on the rank order of student
   scores. Workplace-based assessment produces higher scores but also has
   little effect on student rank order. Further studies are necessary to
   replicate these findings in other settings and demonstrate that student
   learning experiences in rural sites, while popular with students,
   translate into required learning outcomes, as measured by summative
   assessments.}},
Publisher = {{AUSTRALIAN RURAL HEALTH EDUC NETWORK}},
Address = {{PO BOX 242, DEAKIN WEST, ACT 2600, AUSTRALIA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Sen Gupta, TK (Reprint Author), James Cook Univ, Sch Med \& Dent, Townsville, Qld 4811, Australia.
   Sen Gupta, T. K.; Kelly, G., James Cook Univ, Sch Med \& Dent, Townsville, Qld 4811, Australia.
   Hays, R. B., Bond Univ, Fac Hlth Sci \& Med, Southport, Qld 4229, Australia.
   Buettner, P. G., Sch Publ Hlth Trop Med \& Rehabil Sci, Townsville, Qld, Australia.}},
Article-Number = {{1511}},
ISSN = {{1445-6354}},
Keywords = {{assessment; clinical teaching; medical education; rural clinical school;
   undergraduate}},
Keywords-Plus = {{PERFORMANCE; EXPERIENCE}},
Research-Areas = {{Public, Environmental \& Occupational Health}},
Web-of-Science-Categories  = {{Public, Environmental \& Occupational Health}},
Cited-References = {{Dornan T, 2007, MED EDUC, V41, P84, DOI 10.1111/j.1365-2929.2006.02652.x.
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Number-of-Cited-References = {{8}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Rural Remote Health}},
Doc-Delivery-Number = {{708DV}},
Unique-ID = {{ISI:000286342700012}},
}

@article{ ISI:000282657300001,
Author = {Dawany, Noor B. and Tozeren, Aydin},
Title = {{Asymmetric microarray data produces gene lists highly predictive of
   research literature on multiple cancer types}},
Journal = {{BMC BIOINFORMATICS}},
Year = {{2010}},
Volume = {{11}},
Month = {{SEP 27}},
Abstract = {{Background: Much of the public access cancer microarray data is
   asymmetric, belonging to datasets containing no samples from normal
   tissue. Asymmetric data cannot be used in standard meta-analysis
   approaches (such as the inverse variance method) to obtain large sample
   sizes for statistical power enrichment. Noting that plenty of normal
   tissue microarray samples exist in studies not involving cancer, we
   investigated the viability and accuracy of an integrated microarray
   analysis approach based on significance analysis of microarrays (merged
   SAM) using a collection of data from separate diseased and normal
   samples.
   Results: We focused on five solid cancer types (colon, kidney, liver,
   lung, and pancreas), where available microarray data allowed us to
   compare meta-analysis and integrated approaches. Our results from the
   merged SAM significantly overlapped gene lists from the validated
   inverse-variance method. Both meta-analysis and merged SAM approaches
   successfully captured the aberrances in the cell cycle that commonly
   occur in the different cancer types. However, the integrated SAM
   analysis replicated the known cancer literature (excluding microarray
   studies) with much more accuracy than the meta-analysis.
   Conclusion: The merged SAM test is a powerful, robust approach for
   combining data from similar platforms and for analyzing asymmetric
   datasets, including those with only normal or only cancer samples that
   cannot be utilized by meta-analysis methods. The integrated SAM approach
   can also be used in comparing global gene expression between various
   subtypes of cancer arising from the same tissue.}},
Publisher = {{BIOMED CENTRAL LTD}},
Address = {{236 GRAYS INN RD, FLOOR 6, LONDON WC1X 8HL, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Tozeren, A (Reprint Author), Drexel Univ, Ctr Integrated Bioinformat, Bossone Res Bldg 711,3102 Market St, Philadelphia, PA 19104 USA.
   Dawany, Noor B.; Tozeren, Aydin, Drexel Univ, Ctr Integrated Bioinformat, Philadelphia, PA 19104 USA.}},
DOI = {{10.1186/1471-2105-11-483}},
Article-Number = {{483}},
ISSN = {{1471-2105}},
Keywords-Plus = {{DIFFERENTIALLY EXPRESSED GENES; PROBE LEVEL DATA; BREAST-CANCER;
   INTEGRATIVE ANALYSIS; COLORECTAL-CANCER; RANK AGGREGATION;
   PROSTATE-CANCER; SET ENRICHMENT; METAANALYSIS; PROFILES}},
Research-Areas = {{Biochemistry \& Molecular Biology; Biotechnology \& Applied
   Microbiology; Mathematical \& Computational Biology}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Biotechnology \& Applied Microbiology;
   Mathematical \& Computational Biology}},
Author-Email = {{aydin.tozeren@drexel.edu}},
Funding-Acknowledgement = {{Calhoun fellowship; BioAdvance funds}},
Funding-Text = {{Authors thank Will Dampier, Erica Golemis, Andres Kriete, Lyle Ungar,
   Andrew Quong, and Ahmet Sacan for useful and insightful inputs. This
   research was supported by Calhoun fellowship to Noor Dawany as well as
   BioAdvance funds to Greater Philadelphia Bioinformatics Alliance.}},
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Number-of-Cited-References = {{57}},
Times-Cited = {{9}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{BMC Bioinformatics}},
Doc-Delivery-Number = {{660QC}},
Unique-ID = {{ISI:000282657300001}},
}

@article{ ISI:000280599600002,
Author = {Soliman, Mohamed A. and Ilyas, Ihab F. and Ben-David, Shalev},
Title = {{Supporting ranking queries on uncertain and incomplete data}},
Journal = {{VLDB JOURNAL}},
Year = {{2010}},
Volume = {{19}},
Number = {{4}},
Pages = {{477-501}},
Month = {{AUG}},
Abstract = {{Large databases with uncertain information are becoming more common in
   many applications including data integration, location tracking, and Web
   search. In these applications, ranking records with uncertain attributes
   introduces new problems that are fundamentally different from
   conventional ranking. Specifically, uncertainty in records' scores
   induces a partial order over records, as opposed to the total order that
   is assumed in the conventional ranking settings. In this paper, we
   present a new probabilistic model, based on partial orders, to
   encapsulate the space of possible rankings originating from score
   uncertainty. Under this model, we formulate several ranking query types
   with different semantics. We describe and analyze a set of efficient
   query evaluation algorithms. We show that our techniques can be used to
   solve the problem of rank aggregation in partial orders under two widely
   adopted distance metrics. In addition, we design sampling techniques
   based on Markov chains to compute approximate query answers. Our
   experimental evaluation uses both real and synthetic data. The
   experimental study demonstrates the efficiency and effectiveness of our
   techniques under various configurations.}},
Publisher = {{SPRINGER}},
Address = {{233 SPRING ST, NEW YORK, NY 10013 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Soliman, MA (Reprint Author), Univ Waterloo, Sch Comp Sci, Waterloo, ON N2L 3G1, Canada.
   Soliman, Mohamed A.; Ilyas, Ihab F.; Ben-David, Shalev, Univ Waterloo, Sch Comp Sci, Waterloo, ON N2L 3G1, Canada.}},
DOI = {{10.1007/s00778-009-0176-8}},
ISSN = {{1066-8888}},
EISSN = {{0949-877X}},
Keywords = {{Ranking; Top-k; Uncertain data; Probabilistic data; Partial orders; Rank
   aggregation; Kendall tau}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Hardware \& Architecture; Computer Science,
   Information Systems}},
Author-Email = {{m2ali@cs.uwaterloo.ca
   ilyas@cs.uwaterloo.ca
   s4bendavid@uwaterloo.ca}},
ORCID-Numbers = {{Ilyas, Ihab/0000-0001-9052-9714}},
Cited-References = {{Abiteboul S., 1987, SIGMOD.
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Number-of-Cited-References = {{39}},
Times-Cited = {{9}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{VLDB J.}},
Doc-Delivery-Number = {{634QZ}},
Unique-ID = {{ISI:000280599600002}},
}

@article{ ISI:000277653000036,
Author = {Dahl, Geir and Minken, Harald},
Title = {{A note on permutations and rank aggregation}},
Journal = {{MATHEMATICAL AND COMPUTER MODELLING}},
Year = {{2010}},
Volume = {{52}},
Number = {{1-2}},
Pages = {{380-385}},
Month = {{JUL}},
Abstract = {{In this brief note we consider rank aggregation, a popular method in
   voting theory, social choice, business decisions, etc. Mathematically
   the problem is to find a permutation-viewed as a vector-that minimizes
   the sum of the l(1)-distances to a given family of permutations. The
   problem may be solved as an assignment problem and we establish several
   properties of optimal solutions in this problem. (C) 2010 Elsevier Ltd.
   All rights reserved.}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Dahl, G (Reprint Author), Univ Oslo, Dept Informat, Ctr Math Applicat, POB 1053 Blindern, NO-0316 Oslo, Norway.
   Dahl, Geir; Minken, Harald, Univ Oslo, Dept Informat, Ctr Math Applicat, NO-0316 Oslo, Norway.}},
DOI = {{10.1016/j.mcm.2010.02.052}},
ISSN = {{0895-7177}},
Keywords = {{Ranking; Voting; Permutations; Assignment problem}},
Research-Areas = {{Computer Science; Mathematics}},
Web-of-Science-Categories  = {{Computer Science, Interdisciplinary Applications; Computer Science,
   Software Engineering; Mathematics, Applied}},
Author-Email = {{geird@math.uio.no}},
Cited-References = {{Ahuja RK, 1993, NETWORK FLOWS THEORY.
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Number-of-Cited-References = {{17}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Math. Comput. Model.}},
Doc-Delivery-Number = {{595ZM}},
Unique-ID = {{ISI:000277653000036}},
}

@article{ ISI:000279362000012,
Author = {Coppersmith, Don and Fleischer, Lisa K. and Rurda, Atri},
Title = {{Ordering by Weighted Number of Wins Gives a Good Ranking for Weighted
   Tournaments}},
Journal = {{ACM TRANSACTIONS ON ALGORITHMS}},
Year = {{2010}},
Volume = {{6}},
Number = {{3}},
Month = {{JUN}},
Abstract = {{We consider the following simple algorithm for feedback arc set problem
   in weighted tournaments: order the vertices by their weighted indegrees.
   We show that this algorithm has an approximation guarantee of 5 if the
   weights satisfy probability constraints ( for any pair of vertices u and
   v, w(uv) + w(vu) = 1). Special cases of the feedback arc set problem in
   such weighted tournaments include the feedback arc set problem in
   unweighted tournaments and rank aggregation. To complement the upper
   bound, for any constant epsilon > 0, we exhibit an infinite family of (
   unweighted) tournaments for which the aforesaid algorithm ( irrespective
   of how ties are broken) has an approximation ratio of 5 - epsilon.}},
Publisher = {{ASSOC COMPUTING MACHINERY}},
Address = {{2 PENN PLAZA, STE 701, NEW YORK, NY 10121-0701 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Coppersmith, D (Reprint Author), IDA, Ctr Commun Res, Princeton, NJ 08540 USA.
   Coppersmith, Don, IDA, Ctr Commun Res, Princeton, NJ 08540 USA.
   Fleischer, Lisa K., Dartmouth Coll, Dept Comp Sci, Hanover, NH 03755 USA.
   Rurda, Atri, SUNY Buffalo, Dept Comp Sci \& Engn, Buffalo, NY 14260 USA.}},
DOI = {{10.1145/1798596.1798608}},
Article-Number = {{55}},
ISSN = {{1549-6325}},
Keywords = {{Algorithms; Theory; Approximation algorithms; Borda's method; feedback
   arc set problem; rank aggregation; tournaments}},
Research-Areas = {{Computer Science; Mathematics}},
Web-of-Science-Categories  = {{Computer Science, Theory \& Methods; Mathematics, Applied}},
Author-Email = {{lkf@cs.dartmouth.edu
   atri@cse.buffalo.edu}},
Funding-Acknowledgement = {{NSF {[}CCF-0515127]}},
Funding-Text = {{L.K. Fleischer was supported in part by NSF grant CCF-0515127.}},
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Number-of-Cited-References = {{24}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{ACM Trans. Algorithms}},
Doc-Delivery-Number = {{618NH}},
Unique-ID = {{ISI:000279362000012}},
}

@article{ ISI:000274140400005,
Author = {Ailon, Nir},
Title = {{Aggregation of Partial Rankings, p-Ratings and Top-m Lists}},
Journal = {{ALGORITHMICA}},
Year = {{2010}},
Volume = {{57}},
Number = {{2}},
Pages = {{284-300}},
Month = {{JUN}},
Abstract = {{We study the problem of aggregating partial rankings. This problem is
   motivated by applications such as meta-searching and information
   retrieval, search engine spam fighting, e-commerce, learning from
   experts, analysis of population preference sampling, committee decision
   making and more. We improve recent constant factor approximation
   algorithms for aggregation of full rankings and generalize them to
   partial rankings. Our algorithms improve constant factor approximation
   with respect to a family of metrics recently proposed in the context of
   comparing partial rankings. We pay special attention to two important
   types of partial rankings: the well-known top-m lists and the more
   general p-ratings which we define. We provide first evidence for
   hardness of aggregating them for constant m, p.}},
Publisher = {{SPRINGER}},
Address = {{233 SPRING ST, NEW YORK, NY 10013 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ailon, N (Reprint Author), Google Res, 76 9th Ave, New York, NY 10011 USA.
   Google Res, New York, NY 10011 USA.}},
DOI = {{10.1007/s00453-008-9211-1}},
ISSN = {{0178-4617}},
Keywords = {{Rank aggregation; Ranking with ties; Approximation algorithms}},
Research-Areas = {{Computer Science; Mathematics}},
Web-of-Science-Categories  = {{Computer Science, Software Engineering; Mathematics, Applied}},
Author-Email = {{nailon@google.com}},
Cited-References = {{AILON N, 2005, TR71905 PRINC U.
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Number-of-Cited-References = {{27}},
Times-Cited = {{12}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{Algorithmica}},
Doc-Delivery-Number = {{550PM}},
Unique-ID = {{ISI:000274140400005}},
}

@article{ ISI:000273676900010,
Author = {Wang, Ying and Zhang, Ping and Zhou, Yun and Yuan, Jun and Liu, Fang and
   Li, Gen},
Title = {{Handover Management in Enhanced MIH Framework for Heterogeneous Wireless
   Networks Environment}},
Journal = {{WIRELESS PERSONAL COMMUNICATIONS}},
Year = {{2010}},
Volume = {{52}},
Number = {{3}},
Pages = {{615-636}},
Month = {{FEB}},
Abstract = {{Vertical handover decision making is one of the key problems in
   heterogeneous networks environment. In IEEE 802.21 standard, a Media
   Independent Handover (MIH) framework is proposed to improve user
   experience of mobile devices by facilitating handover in heterogeneous
   networks with measurements and triggers from link layers. However,
   vertical handover decision making can benefit from the information more
   than link layers. In this paper, an Enhanced Media Independent Handover
   (EMIH) framework is proposed by integrating more information from
   application layers, user context and network context. Given such
   information, there is also another important problem on how to select a
   favorite network. Two quite important problems from realistic scenario
   are as follows: (1) how to make use of partial knowledge due to
   incomplete value measurement on decision factors; (2) how to deal with
   robustness problem due to inaccurate measurement on decision factors. In
   order to tackle these problems, two novel Weighted Markov Chain (WMC)
   approaches based on rank aggregation are proposed in this paper, in
   which a favorite network is selected as the top one of rank aggregation
   result fused from multiple ranking lists based on decision factors.
   Moreover, an entropy weighting method, combined with WMC approach, is
   studied. The simulations demonstrate the effectiveness of these proposed
   approaches.}},
Publisher = {{SPRINGER}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Wang, Y (Reprint Author), Beijing Univ Posts \& Telecommun, Minist Educ, Key Lab Universal Wireless Commun, Beijing 100088, Peoples R China.
   Wang, Ying; Zhang, Ping; Zhou, Yun; Yuan, Jun; Liu, Fang; Li, Gen, Beijing Univ Posts \& Telecommun, Minist Educ, Key Lab Universal Wireless Commun, Beijing 100088, Peoples R China.}},
DOI = {{10.1007/s11277-008-9628-5}},
ISSN = {{0929-6212}},
Keywords = {{Heterogeneous wireless networks; Vertical handover decision; Network
   selection; Rank aggregation}},
Keywords-Plus = {{MEDIA-INDEPENDENT HANDOVER}},
Research-Areas = {{Telecommunications}},
Web-of-Science-Categories  = {{Telecommunications}},
Author-Email = {{wangying@bupt.edu.cn}},
Funding-Acknowledgement = {{National Nature Science Foundation of China {[}60772112, 60632030,
   60496312]; National 863 Project {[}2006AA01Z260]}},
Funding-Text = {{This research is supported by project of National Nature Science
   Foundation of China (No. 60772112, 60632030, 60496312) and National 863
   Project (2006AA01Z260). The authors of this paper thank Dr. Wei Li and
   Lei Zheng for their helpful discussions and suggestions. Their supports
   are gratefully acknowledged.}},
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Number-of-Cited-References = {{24}},
Times-Cited = {{17}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Wirel. Pers. Commun.}},
Doc-Delivery-Number = {{544RO}},
Unique-ID = {{ISI:000273676900010}},
}

@article{ ISI:000275401000001,
Author = {Mallona, Izaskun and Lischewski, Sandra and Weiss, Julia and Hause,
   Bettina and Egea-Cortines, Marcos},
Title = {{Validation of reference genes for quantitative real-time PCR during leaf
   and flower development in Petunia hybrida}},
Journal = {{BMC PLANT BIOLOGY}},
Year = {{2010}},
Volume = {{10}},
Month = {{JAN 7}},
Abstract = {{Background: Identification of genes with invariant levels of gene
   expression is a prerequisite for validating transcriptomic changes
   accompanying development. Ideally expression of these genes should be
   independent of the morphogenetic process or environmental condition
   tested as well as the methods used for RNA purification and analysis.
   Results: In an effort to identify endogenous genes meeting these
   criteria nine reference genes (RG) were tested in two Petunia lines
   (Mitchell and V30). Growth conditions differed in Mitchell and V30, and
   different methods were used for RNA isolation and analysis. Four
   different software tools were employed to analyze the data. We merged
   the four outputs by means of a non-weighted unsupervised rank
   aggregation method. The genes identified as optimal for transcriptomic
   analysis of Mitchell and V30 were EF1 alpha in Mitchell and CYP in V30,
   whereas the least suitable gene was GAPDH in both lines.
   Conclusions: The least adequate gene turned out to be GAPDH indicating
   that it should be rejected as reference gene in Petunia. The absence of
   correspondence of the best-suited genes suggests that assessing
   reference gene stability is needed when performing normalization of data
   from transcriptomic analysis of flower and leaf development.}},
Publisher = {{BIOMED CENTRAL LTD}},
Address = {{236 GRAYS INN RD, FLOOR 6, LONDON WC1X 8HL, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Egea-Cortines, M (Reprint Author), Univ Politecn Cartagena UPCT, Inst Tecnol Vegetal, Cartagena 30203, Spain.
   Mallona, Izaskun; Weiss, Julia; Egea-Cortines, Marcos, Univ Politecn Cartagena UPCT, Inst Tecnol Vegetal, Cartagena 30203, Spain.
   Lischewski, Sandra; Hause, Bettina, Leibniz Inst Pflanzenbiochem, D-06120 Halle, Saale, Germany.}},
DOI = {{10.1186/1471-2229-10-4}},
Article-Number = {{4}},
ISSN = {{1471-2229}},
Keywords-Plus = {{RT-PCR; HOUSEKEEPING GENES; INTERNAL CONTROL; RELATIVE EXPRESSION;
   CELL-DIVISION; MODEL SYSTEM; TARGET GENES; NORMALIZATION; SELECTION;
   IDENTIFICATION}},
Research-Areas = {{Plant Sciences}},
Web-of-Science-Categories  = {{Plant Sciences}},
Author-Email = {{marcos.egea@upct.es}},
ResearcherID-Numbers = {{Mallona, Izaskun/A-7969-2011
   Egea-Cortines, Marcos/C-3991-2009}},
ORCID-Numbers = {{Mallona, Izaskun/0000-0002-2853-7526
   Egea-Cortines, Marcos/0000-0003-4693-9948}},
Funding-Acknowledgement = {{BIOCARM; MEC {[}AGL2007-61384]; Fundacion Seneca; Spanish Ministry of
   Education {[}MCD-2005-00339]}},
Funding-Text = {{Work performed in the lab of MEC and JW was funded by BIOCARM ( Project
   Bananasai) and MEC (Project AGL2007-61384). IM obtained a PhD fellowship
   from the Fundacion Seneca. This work was performed in partial fulfilment
   of the PhD degree of IM in the framework of the MSc-PhD program with
   Quality mention from the Spanish Ministry of Education MCD-2005-00339.
   Work performed in the lab of BH was funded by the ``Pact for Research
   and Innovation{''} of the Leibniz Society, Germany. Thanks to Ronald
   Koes and Francesca Quatroccio for providing seeds of line V30, and Tom
   Gerats for seeds of line Mitchell. Michiel Vandenbussche is acknowledged
   for primers of GAPDH. Thanks to Luciana Delgado-Benarroch, Juana Mar a
   Gomez Ballester and Mar a Manchado-Rojo for comments on the manuscript.
   Our special thanks to Judith Strommer for helping with the edition of
   the manuscript and advice.}},
Cited-References = {{Pfaffl MW, 2002, NUCLEIC ACIDS RES, V30, DOI 10.1093/nar/30.9.e36.
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   Exposito-Rodriguez M, 2008, BMC PLANT BIOL, V8, DOI 10.1186/1471-2229-8-131.
   Gerats T, 2009, PETUNIA EVOLUTIONARY.
   Hellemans J, 2007, GENOME BIOL, V8, DOI 10.1186/gb-2007-8-2-r19.
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   Jian B, 2008, BMC MOL BIOL, V9, DOI 10.1186/1471-2199-9-59.
   Jian B, 2008, BMC MOL BIOL, V9.
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   Olsvik PA, 2005, BMC MOL BIOL, V6, DOI 10.1186/1471-2199-6-21.
   Paolacci AR, 2009, BMC MOL BIOL, V10, DOI 10.1186/1471-2199-10-11.
   Pihur V, 2009, BMC BIOINFORMATICS, V10, DOI 10.1186/1471-2105-10-62.
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Number-of-Cited-References = {{42}},
Times-Cited = {{86}},
Usage-Count-(Last-180-days) = {{6}},
Usage-Count-Since-2013 = {{25}},
Journal-ISO = {{BMC Plant Biol.}},
Doc-Delivery-Number = {{566VJ}},
Unique-ID = {{ISI:000275401000001}},
}

@article{ ISI:000271826700002,
Author = {Jegou, Herve and Schmid, Cordelia and Harzallah, Hedi and Verbeek, Jakob},
Title = {{Accurate Image Search Using the Contextual Dissimilarity Measure}},
Journal = {{IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE}},
Year = {{2010}},
Volume = {{32}},
Number = {{1}},
Pages = {{2-11}},
Month = {{JAN}},
Abstract = {{This paper introduces the contextual dissimilarity measure, which
   significantly improves the accuracy of bag-of-features-based image
   search. Our measure takes into account the local distribution of the
   vectors and iteratively estimates distance update terms in the spirit of
   Sinkhorn's scaling algorithm, thereby modifying the neighborhood
   structure. Experimental results show that our approach gives
   significantly better results than a standard distance and outperforms
   the state of the art in terms of accuracy on the Nister-Stewenius and
   Lola data sets. This paper also evaluates the impact of a large number
   of parameters, including the number of descriptors, the clustering
   method, the visual vocabulary size, and the distance measure. The
   optimal parameter choice is shown to be quite context-dependent. In
   particular, using a large number of descriptors is interesting only when
   using our dissimilarity measure. We have also evaluated two novel
   variants: multiple assignment and rank aggregation. They are shown to
   further improve accuracy at the cost of higher memory usage and lower
   efficiency.}},
Publisher = {{IEEE COMPUTER SOC}},
Address = {{10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Jegou, H (Reprint Author), INRIA Grenoble, 655 Ave Europe, F-38334 Saint Ismier, France.
   Jegou, Herve; Schmid, Cordelia; Harzallah, Hedi; Verbeek, Jakob, INRIA Grenoble, F-38334 Saint Ismier, France.}},
DOI = {{10.1109/TPAMI.2008.285}},
ISSN = {{0162-8828}},
Keywords = {{Image search; image retrieval; distance regularization}},
Keywords-Plus = {{DOUBLY STOCHASTIC MATRICES}},
Research-Areas = {{Computer Science; Engineering}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Engineering, Electrical \&
   Electronic}},
Author-Email = {{herve.jegou@inria.fr
   cordelia.schmid@inria.fr
   hedi.harzallah@inria.fr
   jakob.verbeek@inria.fr}},
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   Weinberger K., 2006, ADV NEURAL INFORM PR, V18, P1473.}},
Number-of-Cited-References = {{20}},
Times-Cited = {{43}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{IEEE Trans. Pattern Anal. Mach. Intell.}},
Doc-Delivery-Number = {{520FQ}},
Unique-ID = {{ISI:000271826700002}},
}

@article{ ISI:000277223400002,
Author = {Lin, Shili},
Title = {{Space Oriented Rank-Based Data Integration}},
Journal = {{STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY}},
Year = {{2010}},
Volume = {{9}},
Number = {{1}},
Abstract = {{Integration of data from multiple omics platforms has become a major
   challenge in studying complex systems and traits. For integrating data
   from multiple platforms, the underlying spaces from which the top ranked
   elements come from are likely to be different. Thus, taking the
   underlying spaces into consideration explicitly is important, as failure
   to do so would lead to inefficient use of data and might render biases
   and/or sub-optimal results. We propose two space oriented classes of
   heuristic algorithms for integrating ranked lists from omic scale data.
   These algorithms are either Borda inspired or Markov chain based that
   take the underlying spaces of the individual ranked lists into account
   explicitly. We applied this set of algorithms to a number of problems,
   including one that aims at aggregating results from three cDNA and two
   Affymetrix gene expression studies in which the underlying spaces
   between Affymetrix and cDNA platforms are clearly different.}},
Publisher = {{BERKELEY ELECTRONIC PRESS}},
Address = {{2809 TELEGRAPH AVENUE, STE 202, BERKELEY, CA 94705 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Lin, SL (Reprint Author), Ohio State Univ, Columbus, OH 43210 USA.
   Ohio State Univ, Columbus, OH 43210 USA.}},
Article-Number = {{20}},
ISSN = {{1544-6115}},
Keywords = {{Borda's method; Markov chain; omic-scale data; rank aggregation; top-k
   lists; underlying space}},
Keywords-Plus = {{PROSTATE-CANCER; GENE-EXPRESSION; MICROARRAY DATA; METAANALYSIS; LISTS}},
Research-Areas = {{Biochemistry \& Molecular Biology; Mathematical \& Computational
   Biology; Mathematics}},
Web-of-Science-Categories  = {{Biochemistry \& Molecular Biology; Mathematical \& Computational
   Biology; Statistics \& Probability}},
Author-Email = {{shili@stat.ohio-state.edu}},
Funding-Acknowledgement = {{NSF {[}DMS-0112050]}},
Funding-Text = {{This work was supported partially by an NSF grant to the Mathematical
   Biosciences Institute DMS-0112050. The author would like to thank two
   referees for their suggestions and comments.}},
Cited-References = {{Luo J, 2001, CANCER RES, V61, P4683.
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   Liu HC, 2008, J BIOMED INFORM, V41, P570, DOI 10.1016/j.jbi.2007.11.005.}},
Number-of-Cited-References = {{21}},
Times-Cited = {{9}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Stat. Appl. Genet. Mol. Biol.}},
Doc-Delivery-Number = {{590KB}},
Unique-ID = {{ISI:000277223400002}},
}

@article{ ISI:000271332200004,
Author = {Betzler, Nadja and Fellows, Michael R. and Guo, Jiong and Niedermeier,
   Rolf and Rosamond, Frances A.},
Title = {{Fixed-parameter algorithms for Kemeny rankings}},
Journal = {{THEORETICAL COMPUTER SCIENCE}},
Year = {{2009}},
Volume = {{410}},
Number = {{45}},
Pages = {{4554-4570}},
Month = {{OCT 28}},
Abstract = {{The computation of Kemeny rankings is central to many applications in
   the context of rank aggregation. Given a set of permutations (votes)
   over a set of candidates, one searches for a ``consensus permutation{''}
   that is ``closest{''} to the given set of permutations. Unfortunately,
   the problem is NP-hard. We provide a broad study of the parameterized
   complexity for computing optimal Kemeny rankings. Besides the three
   obvious parameters ``number of votes{''}, ``number of candidates{''},
   and solution size (called Kemeny score), we consider further structural
   parameterizations. More specifically, we show that the Kemeny score (and
   a corresponding Kemeny ranking) of an election can be computed
   efficiently whenever the average pairwise distance between two input
   votes is not too large. In other words, KEMENY SCORE is fixed-parameter
   tractable with respect to the parameter ``average pairwise Kendall-Tau
   distance d(a){''}. We describe a fixed-parameter algorithm with running
   time 16(inverted right perpendiculardainverted left perpendicular).
   poly. Moreover, we extend our studies to the parameters ``maximum
   range{''} and ``average range{''} of positions a candidate takes in the
   input votes. Whereas KEMENY SCORE remains fixed-parameter tractable with
   respect to the parameter ``maximum range{''}, it becomes NP-complete in
   the case of an average range of two. This excludes fixed-parameter
   tractability with respect to the parameter ``average range{''} unless P
   = NP. Finally, we extend some of our results to votes with ties and
   incomplete votes, where in both cases one no longer has permutations as
   input. (C) 2009 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Betzler, N (Reprint Author), Univ Jena, Inst Informat, Ernst Abbe Pl 2, D-07743 Jena, Germany.
   Betzler, Nadja; Guo, Jiong; Niedermeier, Rolf, Univ Jena, Inst Informat, D-07743 Jena, Germany.
   Fellows, Michael R.; Rosamond, Frances A., Univ Newcastle, PC Res Unit, Off DVC Res, Callaghan, NSW 2308, Australia.}},
DOI = {{10.1016/j.tcs.2009.08.033}},
ISSN = {{0304-3975}},
Keywords = {{Computational social choice; Voting systems; Winner determination; Rank
   aggregation; Consensus finding; Fixed-parameter tractability}},
Keywords-Plus = {{TRACTABLE ALGORITHMS; COMPLEXITY; ELECTIONS; MAXCUT}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Theory \& Methods}},
Author-Email = {{nadja.betzler@uni-jena.de
   michael.fellows@newcastle.edu.au
   jiong.guo@uni-jena.de
   rolf.niedermeier@uni-jena.de
   frances.rosamond@newcastle.edu.au}},
ResearcherID-Numbers = {{Rosamond, Frances/D-5588-2013}},
ORCID-Numbers = {{Fellows, Michael/0000-0002-6148-9212
   Rosamond, Frances/0000-0002-5097-9929}},
Funding-Acknowledgement = {{Deutsche Forschungsgemeinschaft {[}NI 369/10, GU 1023/1, NI 369/4];
   Australian Research Council}},
Funding-Text = {{The first author was Supported by the Deutsche Forschungsgemeinschaft,
   project PAWS (parameterized algorithmics for voting systems, NI 369/10)
   and project DARE (data reduction and problem kernels, GU 1023/1). The
   second author was supported by the Australian Research Council. This
   work has been carried out while he was staying in Jena as a recipient of
   a Humboldt Research Award of the Alexander von Humboldt foundation,
   Bonn, Germany. The third author was partially supported by the Deutsche
   Forschungsgemeinschaft, Emmy Noether research group PIAF
   (fixed-parameter algorithms, NI 369/4). The fifth author was supported
   by the Australian Research Council.}},
Cited-References = {{Ailon N, 2008, J ACM, V55, DOI 10.1145/1411509.1411513.
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   Kenyon-Mathieu Claire, 2007, Proceedings of the 39th Annual ACM Symposium on Theory of Computing. STOC'07, DOI 10.1145/1250790.1250806.
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   Komusiewicz C, 2009, LECT NOTES COMPUT SC, V5577, P207, DOI 10.1007/978-3-642-02441-2\_19.
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   VANZUYLEN A, 2007, LNCS, V4927, P260.}},
Number-of-Cited-References = {{34}},
Times-Cited = {{19}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Theor. Comput. Sci.}},
Doc-Delivery-Number = {{513OL}},
Unique-ID = {{ISI:000271332200004}},
}

@article{ ISI:000271709500011,
Author = {Xu, YeJun and Da, QingLi and Liu, LiHua},
Title = {{Normalizing rank aggregation method for priority of a fuzzy preference
   relation and its effectiveness}},
Journal = {{INTERNATIONAL JOURNAL OF APPROXIMATE REASONING}},
Year = {{2009}},
Volume = {{50}},
Number = {{8}},
Pages = {{1287-1297}},
Month = {{SEP}},
Abstract = {{The aim of this paper is to show that the normalizing rank aggregation
   method can not only be used to derive the priority vector for a
   Multiplicative preference relation, but also for the additive transitive
   fuzzy preference relation. To do so, a simple functional equation
   between fuzzy preference's element and priority weight is derived
   firstly, then, based on the equation, three methods are proposed to
   prove that the normalizing rank aggregation method is simple and
   effective for deriving the priority vector. Finally, a numerical example
   is used to illustrate the proposed methods. Crown Copyright (C) 2009
   Published by Elsevier Inc. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE INC}},
Address = {{360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Xu, YJ (Reprint Author), HoHai Univ, Sch Business, Nanjing 210098, Peoples R China.
   Xu, YeJun; Liu, LiHua, HoHai Univ, Sch Business, Nanjing 210098, Peoples R China.
   Xu, YeJun; Da, QingLi, Southeast Univ, Sch Econ \& Management, Nanjing 210096, Peoples R China.}},
DOI = {{10.1016/j.ijar.2009.06.008}},
ISSN = {{0888-613X}},
Keywords = {{Fuzzy relation; Multi-attribute decision making; Normalizing rank
   aggregation method; Priority}},
Keywords-Plus = {{GROUP DECISION-MAKING; ANALYTIC HIERARCHY PROCESS; CHI-SQUARE METHOD;
   CONSISTENCY; VECTOR; AHP; ALTERNATIVES; INFORMATION; MODELS}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence}},
Author-Email = {{xuyejohn@163.com}},
Cited-References = {{CRAWFORD G, 1985, J MATH PSYCHOL, V29, P387, DOI 10.1016/0022-2496(85)90002-1.
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   Chiclana F, 1998, FUZZY SET SYST, V97, P33, DOI 10.1016/S0165-0114(96)00339-9.
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Number-of-Cited-References = {{34}},
Times-Cited = {{31}},
Usage-Count-(Last-180-days) = {{5}},
Usage-Count-Since-2013 = {{15}},
Journal-ISO = {{Int. J. Approx. Reasoning}},
Doc-Delivery-Number = {{518QZ}},
Unique-ID = {{ISI:000271709500011}},
}

@article{ ISI:000269484000006,
Author = {van Zuylen, Anke and Williamson, David P.},
Title = {{Deterministic Pivoting Algorithms for Constrained Ranking and Clustering
   Problems}},
Journal = {{MATHEMATICS OF OPERATIONS RESEARCH}},
Year = {{2009}},
Volume = {{34}},
Number = {{3}},
Pages = {{594-620}},
Month = {{AUG}},
Note = {{5th International Workshop on Approximation and Online Algorithms,
   Eilat, ISRAEL, OCT 11-12, 2007}},
Abstract = {{We consider ranking and clustering problems related to the aggregation
   of inconsistent information, in particular, rank aggregation, (weighted)
   feedback arc set in tournaments, consensus and correlation clustering,
   and hierarchical clustering. Ailon et al. {[}Ailon, N., M. Charikar, A.
   Newman. 2005. Aggregating inconsistent information: Ranking and
   clustering. Proc. 37th Annual ACM Sympos. Theory Comput. (STOC `05),
   684-693], Ailon and Charikar {[}Ailon, N., M. Charikar. 2005. Fitting
   tree metrics: Hierarchical clustering and phylogeny. Proc. 46th Annual
   IEEE Sympos. Foundations Comput. Sci. (FOCS `05), 73-82], and Ailon
   {[}Ailon, N. 2007. Aggregation of partial rankings, p-ratings and top-m
   lists. Proc. 18th Annual ACM-SIAM Sympos. Discrete Algorithms (SODA
   `07), 415-424] proposed randomized constant factor approximation
   algorithms for these problems, which recursively generate a solution by
   choosing a random vertex as ``pivot{''} and dividing the remaining
   vertices into two groups based on the pivot vertex.
   In this paper, we answer an open question in these works by giving
   deterministic approximation algorithms for these problems. The analysis
   of our algorithms is simpler than the analysis of the randomized
   algorithms. In addition, we consider the problem of finding minimum-cost
   rankings and clusterings that must obey certain constraints (e. g., an
   input partial order in the case of ranking problems), which were
   introduced by Hegde and Jain {[}Hegde, R., K. Jain. 2006. Personal
   communication]. We show that the first type of algorithms we propose can
   also handle these constrained problems. In addition, we show that in the
   case of a rank aggregation or consensus clustering problem, if the input
   rankings or clusterings obey the constraints, then we can always ensure
   that the output of any algorithm obeys the constraints without
   increasing the objective value of the solution.}},
Publisher = {{INFORMS}},
Address = {{7240 PARKWAY DR, STE 310, HANOVER, MD 21076-1344 USA}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{van Zuylen, A (Reprint Author), Tsinghua Univ, Inst Theoret Comp Sci, Beijing 100084, Peoples R China.
   van Zuylen, Anke, Tsinghua Univ, Inst Theoret Comp Sci, Beijing 100084, Peoples R China.
   Williamson, David P., Cornell Univ, Sch Operat Res \& Informat Engn, Ithaca, NY 14853 USA.}},
DOI = {{10.1287/moor.1090.0385}},
ISSN = {{0364-765X}},
Keywords = {{rank aggregation; minimum feedback arc set in tournaments; consensus
   clustering; correlation clustering; hierarchical clustering;
   approximation algorithm; derandomization}},
Keywords-Plus = {{NP-HARD; TOURNAMENTS; TREE}},
Research-Areas = {{Operations Research \& Management Science; Mathematics}},
Web-of-Science-Categories  = {{Operations Research \& Management Science; Mathematics, Applied}},
Author-Email = {{anke@tsinghua.edu.cn
   dpw@cs.cornell.edu}},
Cited-References = {{Agrawal M, 2004, ANN MATH, V160, P781.
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   HEGDE R, COMMUNICATION.
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   Wakabayashi Y., 1998, RESENHAS IME USP, V3, P323.}},
Number-of-Cited-References = {{35}},
Times-Cited = {{19}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{9}},
Journal-ISO = {{Math. Oper. Res.}},
Doc-Delivery-Number = {{490FL}},
Unique-ID = {{ISI:000269484000006}},
}

@article{ ISI:000269817100001,
Author = {Kothari, Anita and Edwards, Nancy and Hamel, Nadia and Judd, Maria},
Title = {{Is research working for you? validating a tool to examine the capacity
   of health organizations to use research}},
Journal = {{IMPLEMENTATION SCIENCE}},
Year = {{2009}},
Volume = {{4}},
Month = {{JUL 23}},
Abstract = {{Background: `Is research working for you? A self-assessment tool and
   discussion guide for health services management and policy
   organizations', developed by the Canadian Health Services Research
   Foundation, is a tool that can help organizations understand their
   capacity to acquire, assess, adapt, and apply research. Objectives were
   to: determine whether the tool demonstrated response variability;
   describe how the tool differentiated between organizations that were
   known to be lower-end or higher-end research users; and describe the
   potential usability of the tool.
   Methods: Thirty-two focus groups were conducted among four sectors of
   Canadian health organizations. In the first hour of the focus group,
   participants individually completed the tool and then derived a group
   consensus ranking on items. In the second hour, the facilitator asked
   about overall impressions of the tool, to identify insights that emerged
   during the review of items on the tool and to elicit comments on
   research utilization. Discussion data were analyzed qualitatively, and
   individual and consensus item scores were analyzed using descriptive and
   non-parametric statistics.
   Results: The tool demonstrated good usability and strong response
   variability. Differences between higher-end and lower-end research use
   organizations on scores suggested that this tool has adequate
   discriminant validity. The group discussion based on the tool was the
   more useful aspect of the exercise, rather than the actual score
   assigned.
   Conclusion: The tool can serve as a catalyst for an important discussion
   about research use at the organizational level; such a discussion, in
   and of itself, demonstrates potential as an intervention to encourage
   processes and supports for research translation.}},
Publisher = {{BIOMED CENTRAL LTD}},
Address = {{236 GRAYS INN RD, FLOOR 6, LONDON WC1X 8HL, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Kothari, A (Reprint Author), Univ Western Ontario, Arthur \& Sonia Labatt Hlth Sci Bldg,Room 222, London, ON N6A 5B9, Canada.
   Kothari, Anita, Univ Western Ontario, London, ON N6A 5B9, Canada.
   Edwards, Nancy, Univ Ottawa, Ottawa, ON K1H 8M5, Canada.
   Hamel, Nadia, Univ Ottawa, Ottawa, ON K1N 6N5, Canada.
   Judd, Maria, Canadian Hlth Serv Res Fdn, Ottawa, ON K1Z 8R1, Canada.}},
DOI = {{10.1186/1748-5908-4-46}},
Article-Number = {{46}},
ISSN = {{1748-5908}},
Keywords-Plus = {{CONCEPTUAL-FRAMEWORK; DETERMINANTS; INNOVATION; CARE}},
Research-Areas = {{Health Care Sciences \& Services}},
Web-of-Science-Categories  = {{Health Care Sciences \& Services; Health Policy \& Services}},
Author-Email = {{akothari@uwo.ca
   nedwards@uottawa.ca
   NadiaH@uottawa.ca
   maria.judd@chsrf.ca}},
Funding-Acknowledgement = {{Ontario Ministry of Health and Long Term Care; Canadian Health Services
   Research Foundation; Canadian Institutes of Health Research; Government
   of Ontario; Fonds de la recherche en sante du Quebec}},
Funding-Text = {{AK holds a Career Scientist award from the Ontario Ministry of Health
   and Long Term Care. NE holds a CHSRF/CIHR Nursing Chair from the
   Canadian Health Services Research Foundation, the Canadian Institutes of
   Health Research and the Government of Ontario. NH holds a doctoral award
   from the Fonds de la recherche en sante du Quebec. The work reported
   here was financially supported through a research grant from the
   Canadian Health Services Research Foundation. Excellent manuscript
   coordination was provided by Michele Menard-Foster from CHSRF. The
   opinions expressed here are those of the authors. Publication does not
   imply any endorsement of these views by either of the participating
   partners of the Community Health Research Unit, or by the Canadian
   Health Services Research Foundation.}},
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Number-of-Cited-References = {{28}},
Times-Cited = {{25}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{Implement. Sci.}},
Doc-Delivery-Number = {{494MI}},
Unique-ID = {{ISI:000269817100001}},
}

@article{ ISI:000267225000007,
Author = {Bilimoria, Karl Y. and Bentrem, David J. and Lillemoe, Keith D. and
   Talamonti, Mark S. and Ko, Clifford Y. and Amer Coll Surg Pancreatic
   Canc},
Title = {{Assessment of Pancreatic Cancer Care in the United States Based on
   Formally Developed Quality Indicators}},
Journal = {{JOURNAL OF THE NATIONAL CANCER INSTITUTE}},
Year = {{2009}},
Volume = {{101}},
Number = {{12}},
Pages = {{848-859}},
Month = {{JUN 16}},
Abstract = {{Pancreatic cancer outcomes vary considerably among hospitals. Assessing
   pancreatic cancer care by using quality indicators could help reduce
   this variability. However, valid quality indicators are not currently
   available for pancreatic cancer management, and a composite assessment
   of the quality of pancreatic cancer care in the United States has not
   been done.
   Potential quality indicators were identified from the literature,
   consensus guidelines, and interviews with experts. A panel of 20
   pancreatic cancer experts ranked potential quality indicators for
   validity based on the RAND/UCLA Appropriateness Methodology. The
   rankings were rated as valid (high or moderate validity) or not valid.
   Adherence with valid indicators at both the patient and the hospital
   levels and a composite measure of adherence at the hospital level were
   assessed using data from the National Cancer Data Base (2004-2005) for
   49 065 patients treated at 1134 hospitals. Summary statistics were
   calculated for each individual candidate quality indicator to assess the
   median ranking and distribution.
   Of the 50 potential quality indicators identified, 43 were rated as
   valid (29 as high and 14 as moderate validity). Of the 43 valid
   indicators, 11 (25.6\%) assessed structural factors, 19 (44.2\%)
   assessed clinical processes of care, four (9.3\%) assessed treatment
   appropriateness, four (9.3\%) assessed efficiency, and five (11.6\%)
   assessed outcomes. Patient-level adherence with individual indicators
   ranged from 49.6\% to 97.2\%, whereas hospital-level adherence with
   individual indicators ranged from 6.8\% to 99.9\%. Of the 10 component
   indicators (contributing 1 point each) that were used to develop the
   composite score, most hospitals were adherent with fewer than half of
   the indicators (median score = 4; interquartile range = 3-5).
   Based on the quality indicators developed in this study, there is
   considerable variability in the quality of pancreatic cancer care in the
   United States. Hospitals can use these indicators to evaluate the
   pancreatic cancer care they provide and to identify potential quality
   improvement opportunities.}},
Publisher = {{OXFORD UNIV PRESS INC}},
Address = {{JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Bilimoria, KY (Reprint Author), Amer Coll Surg, Canc Programs, 633 N St Clair St,22nd Floor, Chicago, IL 60611 USA.
   Bilimoria, Karl Y.; Ko, Clifford Y., Amer Coll Surg, Canc Programs, Chicago, IL 60611 USA.
   Bilimoria, Karl Y.; Bentrem, David J.; Talamonti, Mark S., Northwestern Univ, Feinberg Sch Med, Dept Surg, Chicago, IL 60611 USA.
   Lillemoe, Keith D., Indiana Univ Sch Med, Dept Surg, Indianapolis, IN USA.
   Talamonti, Mark S., NorthShore Univ Hlth Syst, Dept Surg, Evanston, IL USA.
   Ko, Clifford Y., Univ Calif Los Angeles, Dept Surg, Los Angeles, CA 90024 USA.
   Ko, Clifford Y., VA Greater Angeles Healthcare Syst, Los Angeles, CA USA.}},
DOI = {{10.1093/jnci/djp107}},
ISSN = {{0027-8874}},
Keywords-Plus = {{NEW-YORK-STATE; HOSPITAL VOLUME; OF-CARE; SURGICAL MORTALITY;
   CARDIAC-SURGERY; UNINTENDED CONSEQUENCES; CARDIOTHORACIC SURGEONS;
   APPROPRIATENESS METHOD; COLORECTAL-CANCER; HEALTH-CARE}},
Research-Areas = {{Oncology}},
Web-of-Science-Categories  = {{Oncology}},
Author-Email = {{kbilimoria@facs.org}},
Funding-Acknowledgement = {{American College of Surgeons, Clinical Scholars in Residence program;
   American Cancer Society, Illinois Division; National Cancer Institute
   {[}NCI-60058-NE]}},
Funding-Text = {{American College of Surgeons, Clinical Scholars in Residence program (to
   K.Y.B); American Cancer Society, Illinois Division (to D. J. B);
   National Cancer Institute (NCI-60058-NE to C.Y.K).}},
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Number-of-Cited-References = {{62}},
Times-Cited = {{40}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{J. Natl. Cancer Inst.}},
Doc-Delivery-Number = {{460XH}},
Unique-ID = {{ISI:000267225000007}},
}

@article{ ISI:000267142700001,
Author = {Shachnai, Hadas and Zhang, Lisa and Matsui, Tomomi},
Title = {{A note on generalized rank aggregation}},
Journal = {{INFORMATION PROCESSING LETTERS}},
Year = {{2009}},
Volume = {{109}},
Number = {{13}},
Pages = {{647-651}},
Month = {{JUN 15}},
Abstract = {{In the classic rank aggregation (RA) problem, we are given L input lists
   with potentially inconsistent orders of n elements: Our goal is to find
   a single order of all elements that minimizes the total number of
   disagreements with the given orders. The problem is well known to be
   NP-hard, already for L = 4. We consider a generalization of RA, where
   each list is associated with a set of orderings, and our goal is to
   choose one ordering per list and to find a permutation of the elements
   that minimizes the total disagreements with the chosen orderings. For
   the case in which the lists completely overlap, i.e. each list contains
   all n elements, we show that a simple Greedy algorithm yields a (2 -
   2/L)-approximation for generalized RA. The case in which the lists only
   partially overlap, i.e. each list contains a subset of the n elements,
   is much harder to approximate. In fact, we show that RA with multiple
   orderings per list and partial overlaps cannot be approximated within
   any bounded ratio. (C) 2009 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Shachnai, H (Reprint Author), Technion Israel Inst Technol, Dept Comp Sci, IL-32000 Haifa, Israel.
   Shachnai, Hadas, Technion Israel Inst Technol, Dept Comp Sci, IL-32000 Haifa, Israel.
   Zhang, Lisa, Lucent Technol, Bell Labs, Murray Hill, NJ 07974 USA.
   Matsui, Tomomi, Chuo Univ, Dept Informat \& Syst Engn, Tokyo 1128551, Japan.}},
DOI = {{10.1016/j.ipl.2009.02.015}},
ISSN = {{0020-0190}},
Keywords = {{Generalized rank aggregation; Master ring; Approximation algorithms}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems}},
Author-Email = {{hadas@cs.technion.ac.il
   ylz@research.bell-labs.com
   matsui@ise.chuo-u.ac.jp}},
ResearcherID-Numbers = {{Matsui, Tomomi/B-8863-2015}},
ORCID-Numbers = {{Matsui, Tomomi/0000-0003-0106-0980}},
Cited-References = {{ACHARYA S, GLOBECOM 2003.
   ACHARYA S, 2004, IN SERVICE OPT UNPUB.
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   AILON N, P SODA 07.
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   VANZUYLEN A, 2005, 1431 ORIE.
   VANZUYLEN A, P SODA 07.}},
Number-of-Cited-References = {{14}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Inf. Process. Lett.}},
Doc-Delivery-Number = {{459WG}},
Unique-ID = {{ISI:000267142700001}},
}

@article{ ISI:000264958900003,
Author = {Biedl, Therese and Brandenburg, Franz J. and Deng, Xiaotie},
Title = {{On the complexity of crossings in permutations}},
Journal = {{DISCRETE MATHEMATICS}},
Year = {{2009}},
Volume = {{309}},
Number = {{7}},
Pages = {{1813-1823}},
Month = {{APR 8}},
Note = {{13th International Symposium on Graph Drawing (GD 2005), Limerick,
   IRELAND, SEP 12-14, 2005}},
Organization = {{Sci Fdn Ireland; intel; Microsoft; Tom Sawyer Software; Natl ICT
   Australia; Enterprise Ireland; Failte Ireland; ILOG; Abslnt; DELL;
   JAMESON; Lucent Technol}},
Abstract = {{We investigate crossing minimization problems for a set of permutations,
   where a crossing expresses a disarrangement between elements. The goal
   is a common permutation pi{*} which minimizes the number of crossings.
   In voting and social science theory this is known as the Kemeny optimal
   aggregation problem minimizing the Kendall-tau distance. This rank
   aggregation problem can be phrased as a one-sided two-layer crossing
   minimization problem for a series of bipartite graphs or for an edge
   coloured bipartite graph, where crossings are counted only for
   monochromatic edges. We contribute the max version of the crossing
   minimization problem, which attempts to minimize the discrimination
   against any permutation. As our results, we correct the construction
   from {[}C. Dwork, R. Kumar, M. Noar, D. Sivakumar, Rank aggregation
   methods for the Web, Proc. WWW10 (2001) 613-622] and prove the
   NP-hardness of the common crossing minimization problem for k = 4
   permutations. Then we establish a 2 - 2/k-approximation, improving the
   previous factor of 2. The max version is shown NP-hard for every k >= 4,
   and there is a 2-approximation. Both approximations are optimal, if the
   common permutation is selected from the given ones. For two permutations
   crossing minimization is solved by inspecting the drawings, whereas it
   remains open for three permutations. (C) 2007 Elsevier B.V. All rights
   reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Brandenburg, FJ (Reprint Author), Univ Passau, Lehrstuhl Informat, D-94030 Passau, Germany.
   Brandenburg, Franz J., Univ Passau, Lehrstuhl Informat, D-94030 Passau, Germany.
   Biedl, Therese, Univ Waterloo, Sch Comp Sci, Waterloo, ON N2L 3G1, Canada.
   Deng, Xiaotie, City Univ Hong Kong, Dept Comp Sci, Kowloon, Hong Kong, Peoples R China.}},
DOI = {{10.1016/j.disc.2007.12.088}},
ISSN = {{0012-365X}},
Keywords = {{Crossing minimization; Rank aggregation; Kendall-tau distance;
   NP-hardness approximations}},
Keywords-Plus = {{GRAPHS; ALGORITHM}},
Research-Areas = {{Mathematics}},
Web-of-Science-Categories  = {{Mathematics}},
Author-Email = {{biedl@uwaterloo.ca
   brandenb@informatik.uni-passau.de
   csdeng@cityu.edu.hk}},
ResearcherID-Numbers = {{Deng, Xiaotie/E-8607-2011}},
ORCID-Numbers = {{Deng, Xiaotie/0000-0003-3189-5989}},
Cited-References = {{Ailon N., 2005, STOC, P684, DOI DOI 10.1145/1060590.1060692.
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   YAMAGUCHI A, 2005, DISCRETE COMPUT GEOM, V33, P565.}},
Number-of-Cited-References = {{22}},
Times-Cited = {{8}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{Discret. Math.}},
Doc-Delivery-Number = {{429ZP}},
Unique-ID = {{ISI:000264958900003}},
}

@article{ ISI:000265604200001,
Author = {Pihur, Vasyl and Datta, Susmita and Datta, Somnath},
Title = {{RankAggreg, an R package for weighted rank aggregation}},
Journal = {{BMC BIOINFORMATICS}},
Year = {{2009}},
Volume = {{10}},
Month = {{FEB 19}},
Abstract = {{Background: Researchers in the field of bioinformatics often face a
   challenge of combining several ordered lists in a proper and efficient
   manner. Rank aggregation techniques offer a general and flexible
   framework that allows one to objectively perform the necessary
   aggregation. With the rapid growth of high-throughput genomic and
   proteomic studies, the potential utility of rank aggregation in the
   context of meta-analysis becomes even more apparent. One of the major
   strengths of rank-based aggregation is the ability to combine lists
   coming from different sources and platforms, for example different
   microarray chips, which may or may not be directly comparable otherwise.
   Results: The RankAggreg package provides two methods for combining the
   ordered lists: the Cross-Entropy method and the Genetic Algorithm. Two
   examples of rank aggregation using the package are given in the
   manuscript: one in the context of clustering based on gene expression,
   and the other one in the context of meta-analysis of prostate cancer
   microarray experiments.
   Conclusion: The two examples described in the manuscript clearly show
   the utility of the RankAggreg package in the current bioinformatics
   context where ordered lists are routinely produced as a result of modern
   high-throughput technologies.}},
Publisher = {{BIOMED CENTRAL LTD}},
Address = {{236 GRAYS INN RD, FLOOR 6, LONDON WC1X 8HL, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Datta, S (Reprint Author), Univ Louisville, Dept Bioinformat \& Biostat, Louisville, KY 40292 USA.
   Pihur, Vasyl; Datta, Susmita; Datta, Somnath, Univ Louisville, Dept Bioinformat \& Biostat, Louisville, KY 40292 USA.}},
DOI = {{10.1186/1471-2105-10-62}},
Article-Number = {{62}},
ISSN = {{1471-2105}},
Keywords-Plus = {{PROSTATE-CANCER; MICROARRAY EXPERIMENTS}},
Research-Areas = {{Biochemistry \& Molecular Biology; Biotechnology \& Applied
   Microbiology; Mathematical \& Computational Biology}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Biotechnology \& Applied Microbiology;
   Mathematical \& Computational Biology}},
Author-Email = {{v0pihu01@louisville.edu
   susmita.datta@louisville.edu
   somnath.datta@louisville.edu}},
Funding-Acknowledgement = {{National Science Foundation {[}DMS-0706965, DMS-0805559]}},
Funding-Text = {{We thank the associate editor and referees for their constructive
   comments and useful suggestions which substantially improved the
   manuscript. This research was supported in parts by grants from the
   National Science Foundation (DMS-0706965 to So D and DMS-0805559 to Su
   D).}},
Cited-References = {{Pihur V, 2008, GENOMICS, V92, P400, DOI 10.1016/j.ygeno.2008.05.003.
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Number-of-Cited-References = {{13}},
Times-Cited = {{59}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{8}},
Journal-ISO = {{BMC Bioinformatics}},
Doc-Delivery-Number = {{439CI}},
Unique-ID = {{ISI:000265604200001}},
}

@article{ ISI:000263057400010,
Author = {Iorio, Francesco and Tagliaferri, Roberto and Di Bernardo, Diego},
Title = {{Identifying Network of Drug Mode of Action by Gene Expression Profiling}},
Journal = {{JOURNAL OF COMPUTATIONAL BIOLOGY}},
Year = {{2009}},
Volume = {{16}},
Number = {{2}},
Pages = {{241-251}},
Month = {{FEB}},
Abstract = {{Drug mode of action (MOA) of novel compounds has been predicted using
   phenotypic features or, more recently, comparing side effect
   similarities. Attempts to use gene expression data in mammalian systems
   have so far met limited success. Here, we built a drug similarity
   network starting from a public reference dataset containing genome-wide
   gene expression profiles (GEPs) following treatments with more than a
   thousand compounds. In this network, drugs sharing a subset of molecular
   targets are connected by an edge or lie in the same community. Our
   approach is based on a novel similarity distance between two compounds.
   The distance is computed by combining GEPs via an original
   rank-aggregation method, followed by a gene set enrichment analysis
   (GSEA) to compute similarity between pair of drugs. The network is
   obtained by considering each compound as a node, and adding an edge
   between two compounds if their similarity distance is below a given
   significance threshold. We show that, despite the complexity and the
   variety of the experimental conditions, our approach is able to identify
   similarities in drug mode of action from GEPs. Our approach can also be
   used for the identification of the MOA of new compounds.}},
Publisher = {{MARY ANN LIEBERT INC}},
Address = {{140 HUGUENOT STREET, 3RD FL, NEW ROCHELLE, NY 10801 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Di Bernardo, D (Reprint Author), TIGEM, Syst \& Synthet Biol Lab, Via Pietro Castellino 111, I-80131 Naples, Italy.
   Iorio, Francesco; Di Bernardo, Diego, TIGEM, Syst \& Synthet Biol Lab, I-80131 Naples, Italy.
   Iorio, Francesco; Tagliaferri, Roberto, Univ Salerno, Dept Math \& Comp Sci, Neural \& Robot Networks NeuRoNe Lab, I-84100 Salerno, Italy.
   Di Bernardo, Diego, Univ Naples Federico 2, Dept Comp Sci \& Syst, Naples, Italy.}},
DOI = {{10.1089/cmb.2008.10TT}},
ISSN = {{1066-5277}},
Keywords = {{connectivity map; drug mode of action; gene set enrichment analysis;
   ranks merging; similarity networks}},
Keywords-Plus = {{CONNECTIVITY MAP; DISCOVERY; TARGET; SIMILARITY}},
Research-Areas = {{Biochemistry \& Molecular Biology; Biotechnology \& Applied
   Microbiology; Computer Science; Mathematical \& Computational Biology;
   Mathematics}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Biotechnology \& Applied Microbiology;
   Computer Science, Interdisciplinary Applications; Mathematical \&
   Computational Biology; Statistics \& Probability}},
Author-Email = {{dibernardo@tigem.it}},
ResearcherID-Numbers = {{di Bernardo, Diego/I-9440-2012
   }},
ORCID-Numbers = {{di Bernardo, Diego/0000-0002-1911-7407
   Iorio, Francesco/0000-0001-7063-8913}},
Funding-Acknowledgement = {{Associazione Italiana Ricerca Cancro ({''}Inferring Gene Networks and
   Compound Mode of Action by Expression Profiling{''}); Fondazione
   TeleThon}},
Funding-Text = {{We wish to thank Luisa Cutillo and Francesco Napolitano for a number of
   insightful discussions. All the figures containing networks have been
   obtained using Cytoscape c. This work was supported by a grant of
   Associazione Italiana Ricerca Cancro ({''}Inferring Gene Networks and
   Compound Mode of Action by Expression Profiling{''}) to D. d. B. and to
   a grant of Fondazione TeleThon to D. d. B.}},
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Number-of-Cited-References = {{20}},
Times-Cited = {{38}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{J. Comput. Biol.}},
Doc-Delivery-Number = {{403BS}},
Unique-ID = {{ISI:000263057400010}},
}

@article{ ISI:000274289000009,
Author = {Adler, Priit and Kolde, Raivo and Kull, Meelis and Tkachenko, Aleksandr
   and Peterson, Hedi and Reimand, Jueri and Vilo, Jaak},
Title = {{Mining for coexpression across hundreds of datasets using novel rank
   aggregation and visualization methods}},
Journal = {{GENOME BIOLOGY}},
Year = {{2009}},
Volume = {{10}},
Number = {{12}},
Abstract = {{We present a web resource MEM (Multi-Experiment Matrix) for gene
   expression similarity searches across many datasets. MEM features large
   collections of microarray datasets and utilizes rank aggregation to
   merge information from different datasets into a single global ordering
   with simultaneous statistical significance estimation. Unique features
   of MEM include automatic detection, characterization and visualization
   of datasets that includes the strongest coexpression patterns. MEM is
   freely available at http://biit.cs.ut.ee/mem/.}},
Publisher = {{BIOMED CENTRAL LTD}},
Address = {{236 GRAYS INN RD, FLOOR 6, LONDON WC1X 8HL, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Vilo, J (Reprint Author), Univ Tartu, Inst Comp Sci, Liivi 2-314, EE-50409 Tartu, Estonia.
   Adler, Priit; Peterson, Hedi, Inst Mol \& Cell Biol, EE-51010 Tartu, Estonia.
   Kolde, Raivo; Kull, Meelis; Tkachenko, Aleksandr; Reimand, Jueri; Vilo, Jaak, Univ Tartu, Inst Comp Sci, EE-50409 Tartu, Estonia.
   Kolde, Raivo; Kull, Meelis; Tkachenko, Aleksandr; Peterson, Hedi; Vilo, Jaak, Quretec, EE-51003 Tartu, Estonia.}},
DOI = {{10.1186/gb-2009-10-12-r139}},
Article-Number = {{R139}},
ISSN = {{1474-760X}},
Keywords-Plus = {{EMBRYONIC STEM-CELLS; GENE-EXPRESSION PROFILES; MICROARRAY DATA; NETWORK
   RECONSTRUCTION; FUNCTIONAL ANNOTATION; DNA-REPLICATION; CANCER-CELLS;
   PROBE LEVEL; IDENTIFICATION; MAINTENANCE}},
Research-Areas = {{Biotechnology \& Applied Microbiology; Genetics \& Heredity}},
Web-of-Science-Categories  = {{Biotechnology \& Applied Microbiology; Genetics \& Heredity}},
Author-Email = {{vilo@ut.ee}},
ResearcherID-Numbers = {{Peterson, Hedi/C-7514-2012
   Vilo, Jaak/A-7183-2008
   }},
ORCID-Numbers = {{Vilo, Jaak/0000-0001-5604-4107
   Kolde, Raivo/0000-0003-2886-6298}},
Funding-Acknowledgement = {{EU {[}LSHG-CT-2005-518254, LSHB-CT-2007-037730]; ERDF; Ustus Agur and
   Artur Lind foundations}},
Funding-Text = {{Authors wish to thank Tambet Arak for technical ingenuity and support,
   Sven Laur for proofreading, Toomas Neuman for initial biological setup
   and Misha Kapushesky for help in ArrayExpress data download. The
   financial support was provided by EU FP6 grants (ENFIN
   LSHG-CT-2005-518254 and COBRED LSHB-CT-2007-037730), ERDF through the
   Estonian Centre of Excellence in Computer Science project and Estonian
   Science Foundation ETF7427. JR acknowledges funding from Ustus Agur and
   Artur Lind foundations.}},
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Number-of-Cited-References = {{56}},
Times-Cited = {{35}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{1}},
Journal-ISO = {{Genome Biol.}},
Doc-Delivery-Number = {{552KP}},
Unique-ID = {{ISI:000274289000009}},
}

@article{ ISI:000261635200004,
Author = {Kruger, H. A. and Kearney, W. D.},
Title = {{Consensus ranking - An ICT security awareness case study}},
Journal = {{COMPUTERS \& SECURITY}},
Year = {{2008}},
Volume = {{27}},
Number = {{7-8}},
Pages = {{254-259}},
Month = {{DEC}},
Abstract = {{There are many disciplines where the problem of consensus ranking plays
   a vital role. Decision-makers are frequently asked to express their
   preferences for a group of objects, e.g. new projects, new products,
   candidates in an election, etc. The basic problem then becomes one of
   combining the individual rankings into a group choice or consensus
   ranking. The objective of this paper is to report on the application of
   two management science methodologies to the problem of identifying the
   most important areas to be included in an Information Communications
   Technology (ICT) security awareness program. The first methodology is
   based on the concept of minimizing the distance (disagreement) between
   individual rankings, while the second one employs a heuristic approach.
   A real-world case study from the mining industry is presented to
   illustrate the methods. (c) 2008 Elsevier Ltd. All rights reserved.}},
Publisher = {{ELSEVIER ADVANCED TECHNOLOGY}},
Address = {{OXFORD FULFILLMENT CENTRE THE BOULEVARD, LANGFORD LANE, KIDLINGTON,
   OXFORD OX5 1GB, OXON, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Kruger, HA (Reprint Author), NW Univ, Sch Comp Stat \& Math Sci, Potchefstroom Campus,Hoffman St,Private Bag X6001, ZA-2520 Potchefstroom, South Africa.
   Kruger, H. A., NW Univ, Sch Comp Stat \& Math Sci, ZA-2520 Potchefstroom, South Africa.}},
DOI = {{10.1016/j.cose.2008.07.001}},
ISSN = {{0167-4048}},
Keywords = {{Information security awareness; Consensus ranking; Assignment problem;
   Maximize agreement heuristic; Decision making}},
Keywords-Plus = {{TECHNOLOGY; FRAMEWORK}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems}},
Author-Email = {{Hennie.Kruger@nwu.ac.za
   kearneys@iinet.net.au}},
Funding-Acknowledgement = {{National Research Foundation in South Africa {[}FA2007030800004]}},
Funding-Text = {{Part of this research was supported by the National Research Foundation
   in South Africa. Grant reference FA2007030800004.}},
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Number-of-Cited-References = {{17}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{1}},
Journal-ISO = {{Comput. Secur.}},
Doc-Delivery-Number = {{382WD}},
Unique-ID = {{ISI:000261635200004}},
}

@article{ ISI:000261460100004,
Author = {Pihur, V. and Datta, Somnath and Datta, Susmital},
Title = {{Finding common genes in multiple cancer types through meta-analysis of
   microarray experiments: A rank aggregation approach}},
Journal = {{GENOMICS}},
Year = {{2008}},
Volume = {{92}},
Number = {{6}},
Pages = {{400-403}},
Month = {{DEC}},
Abstract = {{Discovering genes involved in multiple types of cancers is of
   significant therapeutic importance. We show that collective evidence for
   such genes can be obtained via a form of meta-analysis that aggregates
   the results (rankings and p values) from various cancer-specific
   microarray experiments. This method is illustrated by a combined
   analysis of 20 microarray experiments. In the aggregated list of top-50
   genes, 36 of them have been implicated in cancer (often multiple
   cancers) genesis in past studies, which also suggests that this list may
   contain some novel cancer genes that may deserve further scrutiny in the
   future. (C) 2008 Elsevier Inc. All rights reserved.}},
Publisher = {{ACADEMIC PRESS INC ELSEVIER SCIENCE}},
Address = {{525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Datta, S (Reprint Author), Univ Louisville, Dept Bioinformat \& Biostat, Louisville, KY 40292 USA.
   Pihur, V.; Datta, Somnath; Datta, Susmital, Univ Louisville, Dept Bioinformat \& Biostat, Louisville, KY 40292 USA.}},
DOI = {{10.1016/j.ygeno.2008.05.003}},
ISSN = {{0888-7543}},
Keywords = {{Microarray; Cancer; Meta-analysis; Rank aggregation; Cross-entropy}},
Keywords-Plus = {{EXPRESSION PATTERNS; P53 MUTATIONS; PIK3CA GENE}},
Research-Areas = {{Biotechnology \& Applied Microbiology; Genetics \& Heredity}},
Web-of-Science-Categories  = {{Biotechnology \& Applied Microbiology; Genetics \& Heredity}},
Author-Email = {{vasyl.pihur@louisville.edu
   somnath.darta@louisville.edu
   susmita.datta@louisville.edu}},
Funding-Acknowledgement = {{United States National Science Foundation}},
Funding-Text = {{This research was partially supported by grants from the United States
   National Science Foundation to S.D. and S.D.}},
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Number-of-Cited-References = {{17}},
Times-Cited = {{24}},
Usage-Count-(Last-180-days) = {{6}},
Usage-Count-Since-2013 = {{11}},
Journal-ISO = {{Genomics}},
Doc-Delivery-Number = {{380IT}},
Unique-ID = {{ISI:000261460100004}},
}

@article{ ISI:000261357500001,
Author = {Ilyas, Ihab F. and Beskales, George and Soliman, Mohamed A.},
Title = {{A Survey of Top-k Query Processing Techniques in Relational Database
   Systems}},
Journal = {{ACM COMPUTING SURVEYS}},
Year = {{2008}},
Volume = {{40}},
Number = {{4}},
Month = {{OCT}},
Abstract = {{Efficient processing of top-k queries is a crucial requirement in many
   interactive environments that involve massive amounts of data. In
   particular, efficient top-k processing in domains such as the Web,
   multimedia search, and distributed systems has shown a great impact on
   performance. In this survey, we describe and classify top- k processing
   techniques in relational databases. We discuss different design
   dimensions in the current techniques including query models, data access
   methods, implementation levels, data and query certainty, and supported
   scoring functions. We show the implications of each dimension on the
   design of the underlying techniques. We also discuss top- k queries in
   XML domain, and show their connections to relational approaches.}},
Publisher = {{ASSOC COMPUTING MACHINERY}},
Address = {{2 PENN PLAZA, STE 701, NEW YORK, NY 10121-0701 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ilyas, IF (Reprint Author), Univ Waterloo, 200 Univ Ave W, Waterloo, ON N2L 3G1, Canada.
   Ilyas, Ihab F.; Beskales, George; Soliman, Mohamed A., Univ Waterloo, Waterloo, ON N2L 3G1, Canada.}},
DOI = {{10.1145/1391729.1391730}},
Article-Number = {{11}},
ISSN = {{0360-0300}},
EISSN = {{1557-7341}},
Keywords = {{Algorithms; Design; Experimentation; Performance; Top-k; rank-aware
   processing; rank aggregation; voting}},
Keywords-Plus = {{WEB-ACCESSIBLE DATABASES; APPROXIMATE; OPTIMIZATION; ALGORITHMS}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Theory \& Methods}},
Author-Email = {{ilyas@uwaterloo.ca
   gbeskale@uwaterloo.ca
   m2ali@uwaterloo.ca}},
ORCID-Numbers = {{Ilyas, Ihab/0000-0001-9052-9714}},
Funding-Acknowledgement = {{Natural Sciences and Engineering Research Council of Canada
   {[}311671-05]}},
Funding-Text = {{Support was provided in part by the Natural Sciences and Engineering
   Research Council of Canada through Grant 311671-05.}},
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Number-of-Cited-References = {{70}},
Times-Cited = {{85}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{10}},
Journal-ISO = {{ACM Comput. Surv.}},
Doc-Delivery-Number = {{378XG}},
Unique-ID = {{ISI:000261357500001}},
}

@article{ ISI:000260916000004,
Author = {Ailon, Nir and Charikar, Moses and Newman, Alantha},
Title = {{Aggregating Inconsistent Information: Ranking and Clustering}},
Journal = {{JOURNAL OF THE ACM}},
Year = {{2008}},
Volume = {{55}},
Number = {{5}},
Month = {{OCT}},
Abstract = {{We address optimization problems in which we are given contradictory
   pieces of input information and the goal is to find a globally
   consistent solution that minimizes the extent of disagreement with the
   respective inputs. Specifically, the problems we address are rank
   aggregation, the feedback arc set problem on tournaments, and
   correlation and consensus clustering. We show that for all these
   problems (and various weighted versions of them), we can obtain improved
   approximation factors using essentially the same remarkably simple
   algorithm. Additionally, we almost settle a long-standing conjecture of
   Bang-Jensen and Thomassen and show that unless NP subset of BPP, there
   is no polynomial time algorithm for the problem of minimum feedback arc
   set in tournaments.}},
Publisher = {{ASSOC COMPUTING MACHINERY}},
Address = {{2 PENN PLAZA, STE 701, NEW YORK, NY 10121-0701 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ailon, N (Reprint Author), Google NY, 4th Floor,76 9th Ave, New York, NY 10011 USA.
   Ailon, Nir, Google NY, New York, NY 10011 USA.
   Charikar, Moses, Princeton Univ, Dept Comp Sci, Princeton, NJ 08540 USA.
   Newman, Alantha, Rutgers State Univ, DIMACS Ctr, Piscataway, NJ 08854 USA.}},
DOI = {{10.1145/1411509.1411513}},
Article-Number = {{23}},
ISSN = {{0004-5411}},
Keywords = {{Algorithms; Theory; Rank aggregation; consensus clustering; correlation
   clustering; minimum feedback arc-set; tournaments}},
Keywords-Plus = {{ALGORITHM; APPROXIMATION; TOURNAMENTS; SETS}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Hardware \& Architecture; Computer Science,
   Information Systems; Computer Science, Software Engineering; Computer
   Science, Theory \& Methods}},
Author-Email = {{nailon@gmail.com
   moses@cs.princeton.edu
   alantha.newman@gmail.com}},
Funding-Acknowledgement = {{Princeton University; National Science Foundation (NSF) ITR
   {[}CCR-0205594]; DOE Early Career Principal Investigator award
   {[}FG02-02ER25540]; NSF CAREER {[}CCR-0237113]}},
Funding-Text = {{The work of N. Ailon was done while he was at Princeton University,
   partly supported by a Princeton University Honorific Fellowship.; M.
   Charikar was supported by a National Science Foundation (NSF) ITR grant
   CCR-0205594, DOE Early Career Principal Investigator award
   DE-FG02-02ER25540, NSF CAREER award CCR-0237113, and Alfred P. Sloan
   fellowship and a Howard B. Wentz Jr. Junior Faculty award.; The work of
   A. Newman was done while she was visiting Princeton University,
   supported by M. Charikar's Alfred P. Sloan fellowship.}},
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Number-of-Cited-References = {{39}},
Times-Cited = {{37}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{J. ACM}},
Doc-Delivery-Number = {{372QJ}},
Unique-ID = {{ISI:000260916000004}},
}

@article{ ISI:000262367100004,
Author = {Dinu, Liviu P. and Popescu, Marius},
Title = {{A Multi-Criteria Decision Method Based on Rank Distance}},
Journal = {{FUNDAMENTA INFORMATICAE}},
Year = {{2008}},
Volume = {{86}},
Number = {{1-2}},
Pages = {{79-91}},
Abstract = {{The multi-criteria decision making process can be summarized as follows.
   Given a pattern d and a set C = \{c(1), c(2), ... , c(m)\} of all m
   possible categories of d, we are interested in predicting its class by
   using a set of n classifiers l(1), l(2), ... , l(n). Each classifier
   produces a ranking of categories. In this paper we propose and test a
   decision method which combines the rankings by using a particular
   method, called rank distance categorization. This method is actually
   based on the rank distance, a metric which was successfully used in
   computational linguistics and bioinformatics. We define the method,
   present some of its mathematical and computational properties and we
   test it on the digit dataset consisting of handwritten numerals ('0',
   ... , `9') extracted from a collection of Dutch utility maps. We compare
   our experimental results with other reported experiments which used the
   same dataset but different combining methods.}},
Publisher = {{IOS PRESS}},
Address = {{NIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Dinu, LP (Reprint Author), Univ Bucharest, Fac Math \& Comp Sci, Acad 14, Bucharest 010014, Romania.
   Dinu, Liviu P.; Popescu, Marius, Univ Bucharest, Fac Math \& Comp Sci, Bucharest 010014, Romania.}},
ISSN = {{0169-2968}},
Keywords = {{rank distance; rank aggregation problem; multi-criteria decision}},
Keywords-Plus = {{AGGREGATION PROBLEM; COMBINATION; STRINGS}},
Research-Areas = {{Computer Science; Mathematics}},
Web-of-Science-Categories  = {{Computer Science, Software Engineering; Mathematics, Applied}},
Author-Email = {{ldinu@funinf.cs.unibuc.ro
   mpopescu@phobos.cs.unibuc.ro}},
ResearcherID-Numbers = {{Popescu, Marius/A-4688-2014}},
Funding-Acknowledgement = {{MEdC-ANCS; PNII-Idei {[}228]; University of Bucharest}},
Funding-Text = {{We would like to thank to Robert Duin for offering the possibility to
   test our method on the same data as (Duin and Tax, 2000). Many thanks to
   Iulian Buzdugan for his help in making the comparative study. MEdC-ANCS,
   PNII-Idei project no. 228 and University of Bucharest have supported
   this research.}},
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Number-of-Cited-References = {{20}},
Times-Cited = {{3}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{1}},
Journal-ISO = {{Fundam. Inform.}},
Doc-Delivery-Number = {{393IN}},
Unique-ID = {{ISI:000262367100004}},
}

@article{ ISI:000250285400007,
Author = {Beg, M. M. Sufyan and Ahmad, Nesar},
Title = {{Web search enhancement by mining user actions}},
Journal = {{INFORMATION SCIENCES}},
Year = {{2007}},
Volume = {{177}},
Number = {{23}},
Pages = {{5203-5218}},
Month = {{DEC 1}},
Abstract = {{Search engines are among the most popular as well as useful services on
   the web. There is a need, however, to cater to the preferences of the
   users when supplying the search results to them. We propose to maintain
   the search profile of each user, on the basis of which the search
   results would be determined. This requires the integration of techniques
   for measuring search quality, learning from the user feedback and biased
   rank aggregation, etc. For the purpose of measuring web search quality,
   the ``user satisfaction{''} is gauged by the sequence in which he picks
   up the results, the time he spends at those documents and whether or not
   he prints, saves, bookmarks, e-mails to someone or copies-and-pastes a
   portion of that document. For rank aggregation, we adopt and evaluate
   the classical fuzzy rank ordering techniques for web applications, and
   also propose a few novel techniques that outshine the existing
   techniques. A ``user satisfaction{''} guided web search procedure is
   also put forward. Learning from the user feedback proceeds in such a way
   that there is an improvement in the ranking of the documents that are
   consistently preferred by the users. As an integration of our work, we
   propose a personalized web search system. (C) 2006 Elsevier Inc. All
   rights reserved.}},
Publisher = {{ELSEVIER SCIENCE INC}},
Address = {{360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Beg, MMS (Reprint Author), Aligarh Muslim Univ, Dept Comp Engn, Aligarh 202002, Uttar Pradesh, India.
   Aligarh Muslim Univ, Dept Comp Engn, Aligarh 202002, Uttar Pradesh, India.
   Indian Inst Technol, Dept Elect Engn, New Delhi 110016, India.}},
DOI = {{10.1016/j.ins.2006.06.011}},
ISSN = {{0020-0255}},
Keywords = {{web usage mining; user feedback; rank aggregation; search quality;
   personalized web searching}},
Keywords-Plus = {{WORLD-WIDE-WEB; AGGREGATION; QUALITY}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems}},
Author-Email = {{pet04msb@amu.ac.in
   nahmad@ee.iitd.ac.in}},
Cited-References = {{Ahmad N., 2002, P INT C ART INT ENG, P363.
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Number-of-Cited-References = {{30}},
Times-Cited = {{17}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Inf. Sci.}},
Doc-Delivery-Number = {{222GX}},
Unique-ID = {{ISI:000250285400007}},
}

@article{ ISI:000247986500002,
Author = {Li, Hua-Gang and Yu, Hailing and Agrawal, Divyakant and El Abbadi, Amr},
Title = {{Progressive ranking of range aggregates}},
Journal = {{DATA \& KNOWLEDGE ENGINEERING}},
Year = {{2007}},
Volume = {{63}},
Number = {{1}},
Pages = {{4-25}},
Month = {{OCT}},
Note = {{7th International Conference on Data Warehousing and Knowledge Discovery
   (DaWaK 2005), Copenhagen, DENMARK, AUG 22-26, 2005}},
Abstract = {{Ranking-aware queries have been gaining much attention recently in many
   applications such as multimedia databases, search engines and data
   streams. They are, however, not only restricted to such applications but
   are also very useful in On-Line Analytical Processing (OLAP)
   applications. In this paper, we introduce aggregation ranking queries in
   OLAP data cubes motivated by an online advertisement tracking data
   warehouse application. These queries aggregate information over a
   specified range and then return the ranked order of the aggregated
   values. For instance, an advertiser might be interested in the top-k
   publishers over the last three months in terms of sales obtained through
   the online advertisements placed on the publishers. They differ from
   range aggregate queries in that range aggregate queries are mainly
   concerned with an aggregate operator such as SUM and MIN/MAX over the
   selected ranges of all dimensions in the data cubes. Existing techniques
   for range aggregate queries are not able to process aggregation ranking
   queries efficiently. Hence, in this paper we propose new algorithms to
   handle this problem. The essence of the proposed algorithms is based on
   both ranking and cumulative information to progressively rank
   aggregation results. Furthermore we empirically evaluate our techniques
   and the experimental results show that the query cost is improved
   significantly. Published by Elsevier B.V.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Li, HG (Reprint Author), Univ Calif Santa Barbara, Dept Comp Sci, Room 3158,Engr I, Santa Barbara, CA 93106 USA.
   Univ Calif Santa Barbara, Dept Comp Sci, Santa Barbara, CA 93106 USA.}},
DOI = {{10.1016/j.datak.2006.10.008}},
ISSN = {{0169-023X}},
Keywords = {{data warehousing; on-line analytical processing; aggregation; data cube}},
Keywords-Plus = {{DATA CUBE; DATABASES; QUERIES}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Computer Science, Information
   Systems}},
Author-Email = {{huagang@cs.ucsb.edu
   hailing@cs.ucsb.edu
   agrawal@cs.ucsb.edu
   amr@cs.ucsb.edu}},
Cited-References = {{Wang W, 2002, PROC INT CONF DATA, P155.
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   Ho C.-T., 1997, P 1997 ACM SIGMOD IN, P73, DOI 10.1145/253260.253274.
   Ilyas I. F., 2002, Proceedings of the Twenty-eighth International Conference on Very Large Data Bases.
   Ilyas Ihab F., 2003, P 29 INT C VER LARG, P754, DOI 10.1016/B978-012722442-8/50072-0.
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   ZADEH LA, 1965, INFORM CONTROL, V8, P338, DOI 10.1016/S0019-9958(65)90241-X.}},
Number-of-Cited-References = {{21}},
Times-Cited = {{3}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{Data Knowl. Eng.}},
Doc-Delivery-Number = {{189JZ}},
Unique-ID = {{ISI:000247986500002}},
}

@article{ ISI:000248655700026,
Author = {Misra, Jatin and Alevizos, Ilias and Hwang, Dachee and Stephanopoulos,
   George and Stepbanopotilosi, Gregory},
Title = {{Linking Physiology and transcriptional profiles by quantitative
   predective models}},
Journal = {{BIOTECHNOLOGY AND BIOENGINEERING}},
Year = {{2007}},
Volume = {{98}},
Number = {{1}},
Pages = {{252-260}},
Month = {{SEP 1}},
Abstract = {{A methodology for the construction of quantitative, predictive models of
   physiology from transcriptional profiles is presented. The method
   utilizes partial least squares (PLS) regression properly modified to
   allow gene pre-selection based on their signal-to-noise ratio (SNR). The
   final set of genes is obtained from a consensus ranking of genes across
   several thousand trials, each carried out with a different set of
   training samples. The method was tested with transcriptional data from a
   large-scale microarray study profiling the effects of high-fat diet on
   the diet-induced obese mouse model C57BL/6j, and the obese-resistant A/J
   mouse model. Quantitative predictive models were constructed for the age
   of the C57BL/6j mice and the A/J mice, and for the insulin and leptin
   levels of the C57B1/6J mice based on transcriptional data of liver
   obtained over a 12-week period. Similarly, models for the growth rate of
   yeast mutants, and the age of Drosophila samples were developed from
   literature data. Specifically, it is demonstrated that highly predictive
   models can be constructed with current levels of precision in DNA
   microarray measurements provided the variation in the physiological
   measurements is controlled. Genes identified by this method are
   important for their ability to collectively predict phenotype. The
   method can be expanded to include various types of physiological or
   cellular data, thus providing an integrative framework for the
   construction of predictive models.}},
Publisher = {{JOHN WILEY \& SONS INC}},
Address = {{111 RIVER ST, HOBOKEN, NJ 07030 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Stephanopoulos, G (Reprint Author), MIT, Dept Chem Engn, Room 56-469, Cambridge, MA 02139 USA.
   MIT, Dept Chem Engn, Cambridge, MA 02139 USA.
   Inst Syst Biol, Seattle, WA USA.
   Univ Padua, Lab Oncohematol, Dept Pediat, Padua, Italy.}},
DOI = {{10.1002/bit.21540}},
ISSN = {{0006-3592}},
Keywords = {{partial least squares; insulin resistance}},
Keywords-Plus = {{PARTIAL LEAST-SQUARES; GENE-EXPRESSION DATA; PATTERNS}},
Research-Areas = {{Biotechnology \& Applied Microbiology}},
Web-of-Science-Categories  = {{Biotechnology \& Applied Microbiology}},
Author-Email = {{gregstep@rnit.edu}},
Cited-References = {{Boulesteix AL, 2007, BRIEF BIOINFORM, V8, P32, DOI 10.1093/bib/bb1016.
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   Boulos M., 2004, INT J HEALTH GEOGR, V3, P1, DOI DOI 10.1186/1476-072X-3-1.
   Dillon W. R., 1984, MULTIVARIATE ANAL.
   Kim JH, 2002, J BIOMED INFORM, V35, P25, DOI 10.1016/S1532-0464(02)00001-1.
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   Nguyen DV, 2005, MATH BIOSCI, V193, P119, DOI 10.1016/j.mbs.2004.10.007.
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   Raab R Michael, 2005, Nutr Metab (Lond), V2, P15, DOI 10.1186/1743-7075-2-15.}},
Number-of-Cited-References = {{18}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Biotechnol. Bioeng.}},
Doc-Delivery-Number = {{198VN}},
Unique-ID = {{ISI:000248655700026}},
}

@article{ ISI:000249890400006,
Author = {Mamoulis, Nikos and Yiu, Man Lung and Cheng, Kit Hung and Cheung, David
   W.},
Title = {{Efficient top-k aggregation of ranked inputs}},
Journal = {{ACM TRANSACTIONS ON DATABASE SYSTEMS}},
Year = {{2007}},
Volume = {{32}},
Number = {{3}},
Month = {{AUG}},
Abstract = {{A top-k query combines different rankings of the same set of objects and
   returns the k objects with the highest combined score according to an
   aggregate function. We bring to light some key observations, which
   impose two phases that any top-k algorithm, based on sorted accesses,
   should go through. Based on them, we propose a new algorithm, which is
   designed to minimize the number of object accesses, the computational
   cost, and the memory requirements of top-k search with monotone
   aggregate functions. We provide an analysis for its cost and show that
   it is always no worse than the baseline ``no random accesses{''}
   algorithm in terms of computations, accesses, and memory required. As a
   side contribution, we perform a space analysis, which indicates the
   memory requirements of top-k algorithms that only perform sorted
   accesses. For the case, where the required space exceeds the available
   memory, we propose disk-based variants of our algorithm. We propose and
   optimize a multiway top-k join operator, with certain advantages over
   evaluation trees of binary top-k join operators. Finally, we define and
   study the computation of top-k cubes and the implementation of roll-up
   and drill-down operations in such cubes. Extensive experiments with
   synthetic and real data show that, compared to previous techniques, our
   method accesses fewer objects, while being orders of magnitude faster.}},
Publisher = {{ASSOC COMPUTING MACHINERY}},
Address = {{2 PENN PLAZA, STE 701, NEW YORK, NY 10121-0701 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Mamoulis, N (Reprint Author), Univ Hong Kong, Dept Comp Sci, Pokfulam Rd, Hong Kong, Hong Kong, Peoples R China.
   Univ Hong Kong, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China.
   Aalborg Univ, Dept Comp Sci, DK-9220 Aalborg, Denmark.}},
DOI = {{10.1145/1272743.1272749}},
Article-Number = {{19}},
ISSN = {{0362-5915}},
EISSN = {{1557-4644}},
Keywords = {{algorithms; experimentation; performance; top-k queries; rank
   aggregation}},
Keywords-Plus = {{COMBINING FUZZY INFORMATION; DATABASES; QUERIES; ALGORITHMS; OPERATOR;
   VIEWS}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Computer Science, Software
   Engineering}},
Author-Email = {{nikos@cs.hku.hk
   mly@cs.aau.dk
   khcheng9@graduate.hku.hk
   dcheung@cs.hku.hk}},
ORCID-Numbers = {{Yiu, Man Lung/0000-0002-9619-4924}},
Cited-References = {{Agrawal R., 2000, P ACM SIGMOD INT C M, P297, DOI 10.1145/342009.335423.
   Gray J, 1997, DATA MIN KNOWL DISC, V1, P29, DOI 10.1023/A:1009726021843.
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   Borzsonyi S, 2001, PROC INT CONF DATA, P421, DOI 10.1109/ICDE.2001.914855.
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   Chang K. C., 2002, P ACM SIGMOD INT C M, P346.
   Chang YC, 2000, P ACM SIGMOD INT C M, P391, DOI 10.1145/342009.335433.
   de Vries A. P., 2002, P ACM SIGMOD INT C M, P322.
   Fagin R, 1999, J COMPUT SYST SCI, V58, P83, DOI 10.1006/jcss.1998.1600.
   Fagin R, 2003, P 2003 ACM SIGMOD IN, P301, DOI DOI 10.1145/872757.872795.
   Guntzer U, 2000, P 26 INT C VER LARG, P419.
   Guntzer U, 2001, P INT C INF TECHN CO, P622.
   Ilyas I. F., 2002, Proceedings of the Twenty-eighth International Conference on Very Large Data Bases.
   Ilyas I.F., 2004, P ACM SIGMOD INT C M, P203, DOI 10.1145/1007568.1007593.
   Ilyas Ihab F., 2003, P 29 INT C VER LARG, P754, DOI 10.1016/B978-012722442-8/50072-0.
   KieBling W., 2002, P 28 INT C VER LARG, P311.
   MAMOULIS N, 2006, P IEEE INT C DAT ENG.
   Mouratidis K., 2006, P ACM SIGMOD, P635, DOI 10.1145/1142473.1142544.
   Natsev A., 2001, Proceedings of the 27th International Conference on Very Large Data Bases.
   Nepal S, 1999, PROC INT CONF DATA, P22, DOI 10.1109/ICDE.1999.754894.
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   TAO Y, 2007, P C VER LARG DAT, V32, P424.}},
Number-of-Cited-References = {{31}},
Times-Cited = {{21}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{ACM Trans. Database Syst.}},
Doc-Delivery-Number = {{216PI}},
Unique-ID = {{ISI:000249890400006}},
}

@article{ ISI:000249289700008,
Author = {Hamdan, Ahmad M. and Al-Omari, Iyad K. and Al-Bitar, Zaid B.},
Title = {{Ranking dental aesthetics and thresholds of treatment need: a comparison
   between patients, parents, and dentists}},
Journal = {{EUROPEAN JOURNAL OF ORTHODONTICS}},
Year = {{2007}},
Volume = {{29}},
Number = {{4}},
Pages = {{366-371}},
Month = {{AUG}},
Abstract = {{The aims of the present study were to compare rankings of dental
   aesthetics and the threshold at which orthodontic treatment would be
   sought among patients, parents, and dentists. A prospective
   cross-sectional study was designed to address these aims. The study
   sample comprised 100 patients and parents and 23 dental specialists. The
   patients were equally divided between males and females and their mean
   age was 14.7 years (standard deviation 2.3 years). The aesthetic
   component (AC) of the Index of Orthodontic Treatment Need (IOTN)
   represented impairment of dental aesthetics. The 10 numbered photographs
   of the AC were cut into equal-sized rectangles and subjects were asked
   to arrange them from `the one that looks best' to `the one that looks
   worst'. The subjects were then presented with the 10 photographs of AC
   in sequence and asked to identify the cut-off point between' teeth that
   need orthodontic treatment' and `no treatment'. Statistical analysis was
   undertaken with a Mann-Whitney test. The results showed that median
   rankings of dental aesthetics were similar among the three groups (P >
   0.05). The median ranking of photographs 1, 2, 3, 4, and 10 were
   identical to the AC of IOTN. The photographs representing IOTN AC 7 and
   8 were allocated the same median rank of 7 and AC 5 and 9 were allocated
   corresponding median ranks of 6 and 8, respectively. There were no
   significant differences in median cut-off points for treatment need
   among the three groups of subjects (P> 0.05), indicating that the mean
   threshold at which treatment would be sought was AC 4.}},
Publisher = {{OXFORD UNIV PRESS}},
Address = {{GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Hamdan, AM (Reprint Author), Univ Birmingham, Sch Dent, Dept Orthodont, St Chads Queensway, Birmingham B4 6NN, W Midlands, England.
   Univ Jordan, Fac Dent, Orthodont Unit, Amman, Jordan.}},
DOI = {{10.1093/ejo/cjm035}},
ISSN = {{0141-5387}},
Keywords-Plus = {{ORTHODONTIC TREATMENT NEED; ORAL HEALTH; INDEX; PERCEPTION; CHILDREN;
   APPEARANCE; COMPONENT; ATTRACTIVENESS; MALOCCLUSION; OPINION}},
Research-Areas = {{Dentistry, Oral Surgery \& Medicine}},
Web-of-Science-Categories  = {{Dentistry, Oral Surgery \& Medicine}},
Author-Email = {{hamdanama@hotmail.com}},
ResearcherID-Numbers = {{Al-bitar, zaid/B-9144-2015
   }},
ORCID-Numbers = {{Al-bitar, zaid/0000-0002-0388-963X
   Al-Omari, Iyad/0000-0002-2245-5626}},
Cited-References = {{Tung AW, 1998, AM J ORTHOD DENTOFAC, V113, P29, DOI 10.1016/S0889-5406(98)70274-4.
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Number-of-Cited-References = {{38}},
Times-Cited = {{12}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Eur. J. Orthodont.}},
Doc-Delivery-Number = {{207ZN}},
Unique-ID = {{ISI:000249289700008}},
}

@article{ ISI:000248620400005,
Author = {Pihur, Vasyl and Datta, Susmita and Datta, Somnath},
Title = {{Weighted rank aggregation of cluster validation measures: a Monte Carlo
   cross-entropy approach}},
Journal = {{BIOINFORMATICS}},
Year = {{2007}},
Volume = {{23}},
Number = {{13}},
Pages = {{1607-1615}},
Month = {{JUL 1}},
Abstract = {{Motivation: Biologists often employ clustering techniques in the
   explorative phase of microarray data analysis to discover relevant
   biological groupings. Given the availability of numerous clustering
   algorithms in the machine-learning literature, an user might want to
   select one that performs the best for his/her data set or application.
   While various validation measures have been proposed over the years to
   judge the quality of clusters produced by a given clustering algorithm
   including their biological relevance, unfortunately, a given clustering
   algorithm can perform poorly under one validation measure while
   outperforming many other algorithms under another validation measure. A
   manual synthesis of results from multiple validation measures is nearly
   impossible in practice, especially, when a large number of clustering
   algorithms are to be compared using several measures. An automated and
   objective way of reconciling the rankings is needed. Results: Using a
   Monte Carlo cross-entropy algorithm, we successfully combine the ranks
   of a set of clustering algorithms under consideration via a weighted
   aggregation that optimizes a distance criterion. The proposed weighted
   rank aggregation allows for a far more objective and automated
   assessment of clustering results than a simple visual inspection. We
   illustrate our procedure using one simulated as well as three real gene
   expression data sets from various platforms where we rank a total of
   eleven clustering algorithms using a combined examination of 10
   different validation measures. The aggregate rankings were found for a
   given number of clusters k and also for an entire range of k.}},
Publisher = {{OXFORD UNIV PRESS}},
Address = {{GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Datta, S (Reprint Author), Univ Louisville, Dept Bioinformat \& Biostat, Louisville, KY 40202 USA.
   Univ Louisville, Dept Bioinformat \& Biostat, Louisville, KY 40202 USA.}},
DOI = {{10.1093/bioinformatics/btm158}},
ISSN = {{1367-4803}},
Keywords-Plus = {{GENE-EXPRESSION DATA}},
Research-Areas = {{Biochemistry \& Molecular Biology; Biotechnology \& Applied
   Microbiology; Computer Science; Mathematical \& Computational Biology;
   Mathematics}},
Web-of-Science-Categories  = {{Biochemical Research Methods; Biotechnology \& Applied Microbiology;
   Computer Science, Interdisciplinary Applications; Mathematical \&
   Computational Biology; Statistics \& Probability}},
Author-Email = {{somnath.datta@louisville.edu
   somnath.datta@louisville.edu}},
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Number-of-Cited-References = {{24}},
Times-Cited = {{35}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Bioinformatics}},
Doc-Delivery-Number = {{198IN}},
Unique-ID = {{ISI:000248620400005}},
}

@article{ ISI:000247699100082,
Author = {Didehvar, Farzad and Eslahchi, Changiz},
Title = {{An algorithm for rank aggregation problem}},
Journal = {{APPLIED MATHEMATICS AND COMPUTATION}},
Year = {{2007}},
Volume = {{189}},
Number = {{2}},
Pages = {{1847-1858}},
Month = {{JUN 15}},
Abstract = {{The rank aggregation problem is an old problem which arises in many
   different settings. Let A = \{1, 2,..., n\} be the set of alternatives.
   Suppose delta(1), delta(...)(2), delta(k) are some individual
   preferences on A. The problem is to find a rank ordering delta such that
   Sigma(1 <= i <= d) (delta,delta(i)) is the minimum among all rank
   orderings, where d is a metric on the set of the rank orderings on A
   defined by Keen. We know that this problem is NP-hard. In this paper, we
   introduce an algorithm such that by using any rank ordering as an input,
   the output is a rank ordering which satisfies the extended Condorcet
   property. Also for a set of individual preferences, we introduce a rank
   ordering such that if we consider it as an input of the algorithm, we
   expect that the output is an optimal rank aggregation. (c) 2006 Elsevier
   Inc. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE INC}},
Address = {{360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Eslahchi, C (Reprint Author), Amir Kabir Univ, Dept Math \& Comp Sci, Tehran, Iran.
   Amir Kabir Univ, Dept Math \& Comp Sci, Tehran, Iran.
   Shahid Beheshty Univ, Dept Math, Tehran, Iran.}},
DOI = {{10.1016/j.amc.2006.12.065}},
ISSN = {{0096-3003}},
Keywords = {{tournament; ranking; expectation matrix}},
Research-Areas = {{Mathematics}},
Web-of-Science-Categories  = {{Mathematics, Applied}},
Author-Email = {{didehvar@cic.aut.ac.ir
   ch-eslahchi@cc.sbu.ac.ir}},
Cited-References = {{BRARTHOLDI JJ, 1989, VOTING SCHEMES IT CA, V6, P157.
   DEBORDA JC, 1781, MEMOIRES ELECTION SC.
   DECONDORCET M, 1785, DECISION READUES PLU.
   DWORK C, P 10.
   Kemeny J., 1959, DAEDALUS, P571.
   Truchon M., 1998, EXTENSION CONDORCET.}},
Number-of-Cited-References = {{6}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Appl. Math. Comput.}},
Doc-Delivery-Number = {{185GJ}},
Unique-ID = {{ISI:000247699100082}},
}

@article{ ISI:000242117400004,
Author = {Cook, Wade D. and Golany, Boaz and Penn, Michal and Raviv, Tal},
Title = {{Creating a consensus ranking of proposals from reviewers' partial
   ordinal rankings}},
Journal = {{COMPUTERS \& OPERATIONS RESEARCH}},
Year = {{2007}},
Volume = {{34}},
Number = {{4}},
Pages = {{954-965}},
Month = {{APR}},
Abstract = {{Peer review of research proposals and articles is an essential element
   in R\&D processes worldwide. In most cases, each reviewer evaluates a
   small subset of the candidate proposals. The review board is then faced
   with the challenge of creating an overall ``consensus{''} ranking on the
   basis of many partial rankings. In this paper we propose a
   branch-and-bound model to support the construction of an aggregate
   ranking from the partial rankings provided by the reviewers. In a recent
   paper we proposed ways to allocate proposals to reviewers so as to
   achieve the maximum possible overlap among the subsets of proposals
   allocated to different reviewers. Here, we develop a special
   branch-and-bound algorithm that utilizes the overlap generated through
   our earlier methods to enable discrimination in ranking the competing
   proposals. The effectiveness and efficiency of the algorithm is
   demonstrated with small numerical examples and tested through an
   extensive simulation experiment. (c) 2005 Elsevier Ltd. All rights
   reserved.}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}},
Type = {{Review}},
Language = {{English}},
Affiliation = {{Cook, WD (Reprint Author), York Univ, Schulich Sch Buiness, N York, ON M3J 1P3, Canada.
   York Univ, Schulich Sch Buiness, N York, ON M3J 1P3, Canada.
   Technion Israel Inst Technol, Fac Ind Engn \& Management, IL-32000 Haifa, Israel.
   Univ British Columbia, Sauder Sch Buiness, Vancouver, BC V6T 1Z2, Canada.}},
DOI = {{10.1016/j.cor.2005.05.030}},
ISSN = {{0305-0548}},
Keywords = {{peer review; branch-and-bound algorithms}},
Keywords-Plus = {{TOURNAMENT; MODEL}},
Research-Areas = {{Computer Science; Engineering; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Computer Science, Interdisciplinary Applications; Engineering,
   Industrial; Operations Research \& Management Science}},
Author-Email = {{wcook@schulich.yorku.ca}},
ResearcherID-Numbers = {{Raviv, Tal/K-4218-2012
   Raviv, Tal/K-2981-2013}},
ORCID-Numbers = {{Raviv, Tal/0000-0002-5960-2386
   Raviv, Tal/0000-0002-5960-2386}},
Cited-References = {{Beg MMS, 2003, WORLD WIDE WEB, V6, P5, DOI 10.1023/A:1022344031752.
   ALI I, 1986, MANAGE SCI, V32, P660, DOI 10.1287/mnsc.32.6.660.
   BOGART KP, 1975, SIAM J APPL MATH, V29, P254, DOI 10.1137/0129023.
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   KIRKWOOD CW, 1985, OPER RES, V33, P38, DOI 10.1287/opre.33.1.38.
   COOK WD, 1982, MANAGE SCI, V28, P621, DOI 10.1287/mnsc.28.6.621.
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   CARDUS D, 1982, MANAGE SCI, V28, P439.
   Cook WD, 1991, ORDINAL INFORM PREFE.
   Cook W.D, 1978, MANAGE SCI, V24, P1721, DOI 10.1287/mnsc.24.16.1721.
   COOK WD, 2005, IN PRESS MANAGEMENT.
   COOK WD, 1990, J OPER RES SOC, V41, P1111, DOI 10.1057/jors.1990.178.
   GOLANY B, 1993, EUR J OPER RES, V69, P210, DOI 10.1016/0377-2217(93)90165-J.
   Isaak G, 2004, INFORM PROCESS LETT, V92, P107, DOI 10.1016/j.ipl.2004.07.001.
   Kemeny J.G, 1962, MATH MODELS SOCIAL S, P9.
   Kendall M.G., 1962, RANK CORRELATION MET.
   Mehlhorn K., 1999, LEDA PLATFORM COMBIN.
   ROUBENS M, 1982, EUR J OPER RES, V10, P51, DOI 10.1016/0377-2217(82)90131-X.}},
Number-of-Cited-References = {{18}},
Times-Cited = {{20}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{10}},
Journal-ISO = {{Comput. Oper. Res.}},
Doc-Delivery-Number = {{106RC}},
Unique-ID = {{ISI:000242117400004}},
}

@article{ ISI:000244332000008,
Author = {Domshlak, Carmel and Gal, Avigdor and Roitman, Haggai},
Title = {{Rank aggregation for automatic schema matching}},
Journal = {{IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING}},
Year = {{2007}},
Volume = {{19}},
Number = {{4}},
Pages = {{538-553}},
Month = {{APR}},
Abstract = {{Schema matching is a basic operation of data integration, and several
   tools for automating it have been proposed and evaluated in the database
   community. Research in this area reveals that there is no single schema
   matcher that is guaranteed to succeed in finding a good mapping for all
   possible domains and, thus, an ensemble of schema matchers should be
   considered. In this paper, we introduce schema metamatching, a general
   framework for composing an arbitrary ensemble of schema matchers and
   generating a list of best ranked schema mappings. Informally, schema
   metamatching stands for computing a ``consensus{''} ranking of
   alternative mappings between two schemata, given the ``individual{''}
   graded rankings provided by several schema matchers. We introduce
   several algorithms for this problem, varying from adaptations of some
   standard techniques for general quantitative rank aggregation to novel
   techniques specific to the problem of schema matching, and to
   combinations of both. We provide a formal analysis of the applicability
   and relative performance of these algorithms and evaluate them
   empirically on a set of real-world schemata.}},
Publisher = {{IEEE COMPUTER SOC}},
Address = {{10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Domshlak, C (Reprint Author), Technion Israel Inst Technol, Fac Ind Engn \& Management, IL-32000 Haifa, Israel.
   Technion Israel Inst Technol, Fac Ind Engn \& Management, IL-32000 Haifa, Israel.}},
DOI = {{10.1109/TDKE.2007.1010}},
ISSN = {{1041-4347}},
EISSN = {{1558-2191}},
Keywords = {{database integration; schema matching; rank aggregation}},
Research-Areas = {{Computer Science; Engineering}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Computer Science, Information
   Systems; Engineering, Electrical \& Electronic}},
Author-Email = {{dcarmel@ie.technion.ac.il
   avigal@ie.technion.ac.il
   haggair@tx.technion.ac.il}},
Cited-References = {{Melnik S, 2002, PROC INT CONF DATA, P117, DOI 10.1109/ICDE.2002.994702.
   Miller RJ, 2001, SIGMOD RECORD, V30, P78.
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   Gal A, 2005, VLDB J, V14, P50, DOI 10.1007/s00778-003-0115-z.
   Bilke A, 2005, PROC INT CONF DATA, P69.
   {[}Anonymous], 2001, P INT C COOP INF SYS.
   Fagin R, 2003, J COMPUT SYST SCI, V66, P614, DOI 10.1016/S0022-0000(03)00026-6.
   {[}Anonymous], 2001, P 9 INT C COOP INF S.
   {[}Anonymous], 2006, J DATA SEMANTICS.
   BERNERSLEE T, 2001, SCI AM           MAY.
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   Dwork C, 2001, P 10 INT C WORLD WID, P613, DOI DOI 10.1145/371920.372165.
   EMBLEY D, 2002, J BRAZILIAN COMPUTIN, V8, P32, DOI 10.1590/S0104-65002002000200004.
   Fagin R, 2001, P 20 ACM SIGMOD SIGA, P102, DOI DOI 10.1145/375551.975567.
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   FLETCHER GHL, 2006, P 10 INTL C EXT DAT, P95.
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   Hamacher H. W., 1985, Annals of Operations Research, V4, DOI 10.1007/BF02022039.
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   HESS A, 2003, P 2 SEM WEB C.
   Hull R., 1997, Proceedings of the Sixteenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, PODS 1997, DOI 10.1145/263661.263668.
   KOIFMAN G, 2004, P VLDB 04 WORKSH INF, P52.
   Madhavan J., 2001, Proceedings of the 27th International Conference on Very Large Data Bases.
   MADHAVAN J, 2002, P 18 NAT C ART INT 1, P80.
   Melnik S., 2003, ACM SIGMOD INT C MAN, P193.
   Melnik S., 2004, GENERIC MODEL MANAGE.
   Miller R. J., 2000, P INT C VER LARG DAT, P77.
   MORK P, 2006, P 22 INTL C DAT ENG, P3.
   Noy N. Fridman, 2000, P 17 NAT C ART INT A, P450.
   Pascoal M, 2003, Q J OPERATIONS RES, V1, P243.
   RODRIGUEZGIANOL.P, 2001, P INTL C CONC MOD ER, P117.
   SRIVASTAVA B, 2003, P INTL C AUT PLANN S.
   XU L, 2006, INFORM SYST, V39, P657.}},
Number-of-Cited-References = {{44}},
Times-Cited = {{21}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{IEEE Trans. Knowl. Data Eng.}},
Doc-Delivery-Number = {{137ZN}},
Unique-ID = {{ISI:000244332000008}},
}

@article{ ISI:000252979800005,
Author = {Manea, Florin and Ploscaru, Calina},
Title = {{A generalization of the Assignment Problem, and its application to the
   Rank Aggregation Problem}},
Journal = {{FUNDAMENTA INFORMATICAE}},
Year = {{2007}},
Volume = {{81}},
Number = {{4}},
Pages = {{459-471}},
Abstract = {{In this paper we propose a generalization of the Assignment Problem.
   First, we describe an algorithm, based on network flow techniques, that
   obtains just one solution of the approached problem; further, we develop
   an algorithm that is able to find all the solutions. Finally, we discuss
   how this general form of the Assignment Problem can be applied in
   solving the Rank Aggregation Problem, in the case of rankings with ties.}},
Publisher = {{IOS PRESS}},
Address = {{NIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Manea, F (Reprint Author), Univ Bucharest, Fac Math \& Comp Sci, Acad 14, Bucharest, Romania.
   Manea, Florin; Ploscaru, Calina, Univ Bucharest, Fac Math \& Comp Sci, Bucharest, Romania.}},
ISSN = {{0169-2968}},
Keywords = {{assignment problem; network flow; ranking; rank aggregation problem}},
Keywords-Plus = {{LANGUAGES; DISTANCE}},
Research-Areas = {{Computer Science; Mathematics}},
Web-of-Science-Categories  = {{Computer Science, Software Engineering; Mathematics, Applied}},
Author-Email = {{flmanea@funinf.cs.unibuc.ro
   calina.ploscaru@gmail.com}},
Cited-References = {{Ahuja RK, 1993, NETWORK FLOWS.
   Dinu LP, 2006, THEOR COMPUT SCI, V359, P455, DOI 10.1016/j.tcs.2006.05.024.
   Dinu LP, 2006, FUND INFORM, V73, P361.
   Cormen T. H., 1990, INTRO ALGORITHMS.
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   Dinu A, 2005, LECT NOTES COMPUT SC, V3406, P785.
   Dinu LP, 2005, FUND INFORM, V64, P135.
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   Dwork C, 2001, P 10 INT C WORLD WID, P613, DOI DOI 10.1145/371920.372165.
   Kuhn H. W., 1955, NAV RES LOG, V2, P83, DOI DOI 10.1002/NAV.3800020109.
   Manea Florin, 2005, Journal of Applied Mathematics and Informatics, V17, P391.
   Mehlhorn K., 1984, DATA STRUCTURES ALGO.}},
Number-of-Cited-References = {{12}},
Times-Cited = {{3}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{1}},
Journal-ISO = {{Fundam. Inform.}},
Doc-Delivery-Number = {{259ZQ}},
Unique-ID = {{ISI:000252979800005}},
}

@article{ ISI:000208762400002,
Author = {Muravyov, Sergey V.},
Title = {{RANKINGS AS ORDINAL SCALE MEASUREMENT RESULTS}},
Journal = {{METROLOGY AND MEASUREMENT SYSTEMS}},
Year = {{2007}},
Volume = {{14}},
Number = {{1, SI}},
Pages = {{9-20}},
Abstract = {{Rankings (or preference relations, or weak orders) are sometimes
   considered to be non-empirical, nonobjective, low-informative and, in
   principle, are not worthy to be titled measurements. A purpose of the
   paper is to demonstrate that the measurement result on the ordinal scale
   should be an entire (consensus) ranking of n objects ranked by m
   properties (or experts, or voters) in order of preference and the
   ranking is one of points of the weak orders space. The consensus
   relation that would give an integrative characterization of the initial
   rankings is one of strict (linear) order relations, which, in some
   sense, is nearest to every of the initial rankings. A recursive branch
   and bound measurement procedure for finding the consensus relation is
   described. An approach to consensus relation uncertainty assessment is
   discussed.}},
Publisher = {{POLISH ACAD SCIENCES COMMITTEE METROLOGY \& RES EQUIPMENT}},
Address = {{UL MIODOWA 10, WARSAW, 00251, POLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Muravyov, SV (Reprint Author), Tomsk Polytech Univ, Dept Computer Aided Measurement Syst \& Metrol, Tomsk, Russia.
   Tomsk Polytech Univ, Dept Computer Aided Measurement Syst \& Metrol, Tomsk, Russia.}},
ISSN = {{0860-8229}},
Keywords = {{Ordinal scale; weak order; consensus relation; recursive algorithm}},
Research-Areas = {{Instruments \& Instrumentation}},
Web-of-Science-Categories  = {{Instruments \& Instrumentation}},
Author-Email = {{muravyov@camsam.tpu.ru}},
Cited-References = {{De Donder P, 2000, MATH SOC SCI, V40, P85, DOI 10.1016/S0165-4896(99)00042-6.
   YOUNG HP, 1978, SIAM J APPL MATH, V35, P285, DOI 10.1137/0135023.
   BARTHELEMY JP, 1989, EUR J OPER RES, V42, P313, DOI 10.1016/0377-2217(89)90442-6.
   Arrow K. J., 1962, SOCIAL CHOICE INDIVI.
   Bryansky L. N., 2004, METROLOGY SCALES STA.
   Cecconi P, 2006, MEASUREMENT, V39, P1, DOI 10.1016/j.measurement.2005.10.012.
   Gordeev E. N., 1996, COMP MATH MATH PHYS, V36, P66.
   Johnson D. S., 1979, COMPUTERS INTRACTABI.
   Kemeny J., 1962, MATH MODELS SOCIAL S.
   Muravyov SV, 2001, MEASUREMENT, V29, P209, DOI 10.1016/S0263-2241(00)00040-3.
   Parker J. R., 1998, 199861506 U CALG DEP.
   Reinelt G., 1985, LINEAR ORDERING PROB.
   Wirth N., 1986, ALGORITHMS DATA STRU.}},
Number-of-Cited-References = {{13}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Metrol. Meas. Syst.}},
Doc-Delivery-Number = {{V29QH}},
Unique-ID = {{ISI:000208762400002}},
}

@article{ ISI:000243396000003,
Author = {Ilyas, Ihab F. and Aref, Walid G. and Elmagarmid, Ahmed K. and Elmongui,
   Hicham G. and Shah, Rahul and Vitter, Jeffrey Scott},
Title = {{Adaptive rank-aware query optimization in relational databases}},
Journal = {{ACM TRANSACTIONS ON DATABASE SYSTEMS}},
Year = {{2006}},
Volume = {{31}},
Number = {{4}},
Pages = {{1257-1304}},
Month = {{DEC}},
Abstract = {{Rank-aware query processing has emerged as a key requirement in modern
   applications. In these applications, efficient and adaptive evaluation
   of top-k queries is an integral part of the application semantics. In
   this article, we introduce a rank-aware query optimization framework
   that fully integrates rank-join operators into relational query engines.
   The framework is based on extending the System R dynamic programming
   algorithm in both enumeration and pruning. We define ranking as an
   interesting physical property that triggers the generation of rank-aware
   query plans. Unlike traditional join operators, optimizing for rank-join
   operators depends on estimating the input cardinality of these
   operators. We introduce a probabilistic model for estimating the input
   cardinality, and hence the cost of a rank-join operator. To our
   knowledge, this is the first effort in estimating the needed input size
   for optimal rank aggregation algorithms. Costing ranking plans is key to
   the full integration of rank-join operators in real-world query
   processing engines.
   Since optimal execution strategies picked by static query optimizers
   lose their optimality due to estimation errors and unexpected changes in
   the computing environment, we introduce several adaptive execution
   strategies for top-k queries that respond to these unexpected changes
   and costing errors. Our reactive reoptimization techniques change the
   execution plan at runtime to significantly enhance the performance of
   running queries. Since top-k query plans are usually pipelined and
   maintain a complex ranking state, altering the execution strategy of a
   running ranking query is an important and challenging task.
   We conduct an extensive experimental study to evaluate the performance
   of the proposed framework. The experimental results are twofold: ( 1) we
   show the effectiveness of our cost-based approach of integrating ranking
   plans in dynamic programming cost-based optimizers; and ( 2) we show a
   significant speedup ( up to 300\%) when using our adaptive execution of
   ranking plans over the state-of-the-art mid-query reoptimization
   strategies.}},
Publisher = {{ASSOC COMPUTING MACHINERY}},
Address = {{2 PENN PLAZA, STE 701, NEW YORK, NY 10121-0701 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ilyas, IF (Reprint Author), Univ Waterloo, 200 Univ Ave W, Waterloo, ON N2L 3G1, Canada.
   Univ Waterloo, Waterloo, ON N2L 3G1, Canada.
   Purdue Univ, W Lafayette, IN 47907 USA.}},
DOI = {{10.1145/1189769.1189772}},
ISSN = {{0362-5915}},
EISSN = {{1557-4644}},
Keywords = {{algorithms; design; experimentation; performance; advanced query
   processing; ranking; top-k; adaptive processing; rank-aware optimization}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Computer Science, Software
   Engineering}},
Author-Email = {{ilyas@uwaterloo.ca}},
ORCID-Numbers = {{Ilyas, Ihab/0000-0001-9052-9714}},
Cited-References = {{AMSALEG L, 1996, DISTRIB PARALLEL DAT, P208.
   Ilyas IF, 2004, VLDB J, V13, P207, DOI 10.1007/s00778-004-0128-2.
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   Ilyas Ihab F., 2003, P 29 INT C VER LARG, P754, DOI 10.1016/B978-012722442-8/50072-0.
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   Natsev A., 2001, Proceedings of the 27th International Conference on Very Large Data Bases.
   Nepal S, 1999, PROC INT CONF DATA, P22, DOI 10.1109/ICDE.1999.754894.
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   ZHUY Y, 2004, P ACM SIGMOD INT C M.}},
Number-of-Cited-References = {{37}},
Times-Cited = {{19}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{ACM Trans. Database Syst.}},
Doc-Delivery-Number = {{124US}},
Unique-ID = {{ISI:000243396000003}},
}

@article{ ISI:000240372000008,
Author = {Hochbaum, Dorit S. and Levin, Asaf},
Title = {{Methodologies and algorithms for group-rankings decision}},
Journal = {{MANAGEMENT SCIENCE}},
Year = {{2006}},
Volume = {{52}},
Number = {{9}},
Pages = {{1394-1408}},
Month = {{SEP}},
Abstract = {{The problem of group ranking, also known as rank aggregation, has been
   studied in contexts varying from sports, to multicriteria decision
   making, to machine learning, to ranking Web pages, and to behavioral
   issues. The dynamics of the group aggregation of individual decisions
   has been a subject of central importance in decision theory. We present
   here a new paradigm using an optimization framework that addresses major
   shortcomings that exist in current models of group ranking. Moreover,
   the framework provides a specific performance measure for the quality of
   the aggregate ranking as per its deviations from the individual
   decision-makers' rankings.
   The new model for the group-ranking problem presented here is based on
   rankings provided with intensity-that is, the degree of preference is
   quantified. The model allows for flexibility in decision protocols and
   can take into consideration imprecise beliefs, less than full confidence
   in some of the rankings, and differentiating between the expertise of
   the reviewers. Our approach relaxes frequently made assumptions of:
   certain beliefs in pairwise rankings; homogeneity implying equal
   expertise of all decision makers with respect to all evaluations; and
   full list requirement according to which each decision maker evaluates
   and ranks all objects. The option of preserving the ranks in certain
   subsets is also addressed in the model here. Significantly, our model is
   a natural extension and generalization of existing models, yet it is
   solvable in polynomial time. The group-rankings models are linked to
   network flow techniques.}},
Publisher = {{INST OPERATIONS RESEARCH  MANAGEMENT SCIENCES}},
Address = {{901 ELKRIDGE LANDING RD, STE 400, LINTHICUM HTS, MD 21090-2909 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Hochbaum, DS (Reprint Author), Univ Calif Berkeley, Dept Ind Engn \& Operat Res, Berkeley, CA 94720 USA.
   Univ Calif Berkeley, Dept Ind Engn \& Operat Res, Berkeley, CA 94720 USA.
   Univ Calif Berkeley, Walter A Haas Sch Business, Berkeley, CA 94720 USA.
   Hebrew Univ Jerusalem, Dept Stat, IL-91905 Jerusalem, Israel.}},
DOI = {{10.1287/mnsc.1060.0540}},
ISSN = {{0025-1909}},
Keywords = {{network flow; group ranking; decision making}},
Keywords-Plus = {{ANALYTIC HIERARCHY PROCESS; NETWORK FLOW PROBLEM; PREFERENCE; CRITERIA;
   THEOREM; CUT}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
Author-Email = {{hochbaum@ieor.berkeley.edu
   levinas@mscc.huji.ac.il}},
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Number-of-Cited-References = {{35}},
Times-Cited = {{30}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{18}},
Journal-ISO = {{Manage. Sci.}},
Doc-Delivery-Number = {{082FL}},
Unique-ID = {{ISI:000240372000008}},
}

@article{ ISI:000239885600032,
Author = {Dinu, Liviu P. and Manea, Florin},
Title = {{An efficient approach for the rank aggregation problem}},
Journal = {{THEORETICAL COMPUTER SCIENCE}},
Year = {{2006}},
Volume = {{359}},
Number = {{1-3}},
Pages = {{455-461}},
Month = {{AUG 14}},
Abstract = {{This paper presents some computational properties of the rank-distance,
   a measure of similarity between partial rankings. We show how this
   distance generalizes the Spearman footrule distance, preserving its good
   computational complexity: the rank-distance between two partial rankings
   can be computed in linear time, and the rank aggregation problem can be
   solved in polynomial time. Further, we present a generalization of the
   rank-distance to strings, which permits to solve the median string
   problem in polynomial time. This appears rather surprising to us given
   the fact that for other non-trivial string distances, such as
   edit-distance, this problem is NP-hard. (C) 2006 Elsevier B.V. All
   rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Manea, F (Reprint Author), Univ Bucharest, Fac Math, Acad 14, Bucharest, Romania.
   Univ Bucharest, Fac Math, Bucharest, Romania.}},
DOI = {{10.1016/j.tcs.2006.05.024}},
ISSN = {{0304-3975}},
Keywords = {{ranking; rank aggregation problem; assignment problem; bipartite
   matching of given cardinality and weight; string distance}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Theory \& Methods}},
Author-Email = {{ldinu@funinf.cs.unibuc.ro
   fimanea@funinf.cs.unibuc.ro}},
Cited-References = {{Ahuja RK, 1993, NETWORK FLOWS.
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Number-of-Cited-References = {{15}},
Times-Cited = {{15}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{0}},
Journal-ISO = {{Theor. Comput. Sci.}},
Doc-Delivery-Number = {{075LD}},
Unique-ID = {{ISI:000239885600032}},
}

@article{ ISI:000240448100015,
Author = {Brodersen, Klaus Peter and Quinlan, Roberto},
Title = {{Midges as palaeoindicators of lake productivity, eutrophication and
   hypolimnetic oxygen}},
Journal = {{QUATERNARY SCIENCE REVIEWS}},
Year = {{2006}},
Volume = {{25}},
Number = {{15-16}},
Pages = {{1995-2012}},
Month = {{AUG}},
Abstract = {{The sedimentary record from lakes can be used as an archive of past
   environmental changes and for events related to anthropogenic activities
   in the catchment area. In this paper, we review the more recent studies
   on zoobenthos responses to changes in lake productivity and to altered
   sublittoral and hypolimnetic oxygen conditions, as reflected from
   subfossil midge (Diptera: Chironomidae) assemblages and
   palaeostratigraphies. We discuss how the importance of different
   environmental variables is scale dependent in both time and space and we
   summarize some of the classical and general patterns in chironomid
   palaeolimnology. The recent advances in quantitative reconstructions
   using chironomid transfer functions and numerical analyses are presented
   and compared. A consensus ranking of species trophic optima and
   respiratory adaptations from published data sets showed good agreement.
   Factors such as lake depth, stratification patterns, water level change,
   sediment conditions, submerged vegetation and ecological thresholds are
   all important for interpretation of palaeolimnological trajectories. We
   use previously published and new data to document how these factors
   determine, change or preserve the ``lake identity{''} over time. We
   conclude that subfossil chironomids have proven to be very effective
   indicators for lake trophic development (productivity) and hypolimnetic
   oxygen conditions. Challenges in interpreting the subfossil chironomid
   record include the interaction between a range of scale-dependent
   variables and processes. (c) 2006 Elsevier Ltd. All rights reserved.}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}},
Type = {{Review}},
Language = {{English}},
Affiliation = {{Brodersen, KP (Reprint Author), Univ Copenhagen, Freshwater Biol Lab, 51 Helsingorsgade, DK-3400 Hillerod, Denmark.
   Univ Copenhagen, Freshwater Biol Lab, DK-3400 Hillerod, Denmark.
   York Univ, Dept Biol, Toronto, ON M3J 1P3, Canada.}},
DOI = {{10.1016/j.quascirev.2005.03.020}},
ISSN = {{0277-3791}},
Keywords-Plus = {{CHIRONOMUS-ANTHRACINUS DIPTERA; WATER-QUALITY CHANGES; LARGE BOREAL
   LAKE; LONG-TERM TRENDS; ALPINE LAKE; MACROINVERTEBRATE COMMUNITIES;
   PALEOLIMNOLOGICAL ASSESSMENT; SUBFOSSIL CHIRONOMIDS; SHALLOW LAKES;
   QUANTITATIVE INFERENCES}},
Research-Areas = {{Physical Geography; Geology}},
Web-of-Science-Categories  = {{Geography, Physical; Geosciences, Multidisciplinary}},
Author-Email = {{kpbrodersen@bi.ku.dk}},
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Number-of-Cited-References = {{153}},
Times-Cited = {{94}},
Usage-Count-(Last-180-days) = {{6}},
Usage-Count-Since-2013 = {{39}},
Journal-ISO = {{Quat. Sci. Rev.}},
Doc-Delivery-Number = {{083HX}},
Unique-ID = {{ISI:000240448100015}},
}

@article{ ISI:000236522400001,
Author = {Cook, WD},
Title = {{Distance-based and ad hoc consensus models in ordinal preference ranking}},
Journal = {{EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}},
Year = {{2006}},
Volume = {{172}},
Number = {{2}},
Pages = {{369-385}},
Month = {{JUL 16}},
Abstract = {{This paper examines the problem of aggregating ordinal preferences on a
   set of alternatives into a consensus. This problem has been the subject
   of study for more than two centuries and many procedures have been
   developed to create a compromise or consensus.
   We examine a variety of structures for preference specification, and in
   each case review the related models for deriving a consensus. Two
   classes of consensus models are discussed, namely ad hoc methods,
   evolving primarily from parliamentary settings over the past 200 years,
   and distance or axiomatic-based methods. We demonstrate the levels of
   complexity of the various distance-based models by presenting the
   related mathematical programming formulations for them. We also present
   conditions for equivalence, that is, for yielding the same consensus
   ranking for some of the methods. Finally, we discuss various extensions
   of the basic ordinal ranking structures, paying specific attention to
   partial ranking, voting member weighted consensus, ranking with
   intensity of preference, and rank correlation methods, as alternative
   approaches to deriving a consensus. Suggestions for future research
   directions are given. (c) 2005 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Review}},
Language = {{English}},
Affiliation = {{Cook, WD (Reprint Author), York Univ, Schulich Sch Business, Dept Management Sci, 4700 Keele St, Toronto, ON M3J 1P3, Canada.
   York Univ, Schulich Sch Business, Dept Management Sci, Toronto, ON M3J 1P3, Canada.}},
DOI = {{10.1016/j.ejor.2005.03.048}},
ISSN = {{0377-2217}},
Keywords = {{ranking; ordinal preferences; distance; consensus; correlation; voters;
   power indices}},
Keywords-Plus = {{DECISION-MAKING; REPRESENTATION; TOURNAMENTS; PRIORITY; MEMBERS}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
Author-Email = {{wcook@schulich.yorku.ca}},
Cited-References = {{ALI I, 1986, MANAGE SCI, V32, P660, DOI 10.1287/mnsc.32.6.660.
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Number-of-Cited-References = {{42}},
Times-Cited = {{75}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{14}},
Journal-ISO = {{Eur. J. Oper. Res.}},
Doc-Delivery-Number = {{028XP}},
Unique-ID = {{ISI:000236522400001}},
}

@article{ ISI:000238751500002,
Author = {DeConde, R and Hawley, S and Falcon, S and Clegg, N and Knudsen, B and
   Etzioni, R},
Title = {{Combining results of microarray experiments: A rank aggregation approach}},
Journal = {{STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY}},
Year = {{2006}},
Volume = {{5}},
Month = {{JUL 2}},
Abstract = {{As technology for microarray analysis becomes widespread, it is becoming
   increasingly important to be able to compare and combine the results of
   experiments that explore the same scientific question. In this article,
   we present a rank-aggregation approach for combining results from
   several microarray studies. The motivation for this approach is twofold;
   first, the final results of microarray studies are typically expressed
   as lists of genes, rank-ordered by a measure of the strength of evidence
   that they are functionally involved in the disease process, and second,
   using the information on this rank-ordered metric means that we do not
   have to concern ourselves with data on the actual expression levels,
   which may not be comparable across experiments. Our approach draws on
   methods for combining top-k lists from the computer science literature
   on meta-search. The meta-search problem shares several important
   features with that of combining microarray experiments, including the
   fact that there are typically few lists with many elements and the
   elements may not be common to all lists. We implement two meta-search
   algorithms, which use a Markov chain framework to convert pairwise
   preferences between list elements into a stationary distribution that
   represents an aggregate ranking (Dwork et al, 2001). We explore the
   behavior of the algorithms in hypothetical examples and a simulated
   dataset and compare their performance with that of an algorithm based on
   the order-statistics model of Thurstone (Thurstone, 1927). We apply all
   three algorithms to aggregate the results of five microarray studies of
   prostate cancer.}},
Publisher = {{BERKELEY ELECTRONIC PRESS}},
Address = {{2809 TELEGRAPH AVENUE, STE 202, BERKELEY, CA 94705 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{DeConde, R (Reprint Author), Fred Hutchinson Canc Res Ctr, Div Publ Hlth Sci, Mailstop M2-B230,1100 Fairview Ave N, Seattle, WA 98109 USA.
   Fred Hutchinson Canc Res Ctr, Div Publ Hlth Sci, Seattle, WA 98109 USA.
   Fred Hutchinson Canc Res Ctr, Program Computat Biol, Seattle, WA 98109 USA.
   Fred Hutchinson Canc Res Ctr, Div Human Biol, Seattle, WA 98109 USA.}},
Article-Number = {{15}},
ISSN = {{1544-6115}},
Keywords = {{rank aggregation; microarrays; meta-analysis; Markov chains;
   order-statistic models}},
Keywords-Plus = {{PROSTATE-CANCER PROGRESSION; GENE-EXPRESSION; METAANALYSIS; BIOMARKERS;
   PROFILES; GROWTH; CELLS}},
Research-Areas = {{Biochemistry \& Molecular Biology; Mathematical \& Computational
   Biology; Mathematics}},
Web-of-Science-Categories  = {{Biochemistry \& Molecular Biology; Mathematical \& Computational
   Biology; Statistics \& Probability}},
Author-Email = {{rdeconde@gmail.com
   shawley@fhcrc.org
   sfalcon@fhcrc.org
   nglegg@fhcrc.org
   bknudsen@fhcrc.org
   retzioni@fhcrc.org}},
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Number-of-Cited-References = {{33}},
Times-Cited = {{37}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Stat. Appl. Genet. Mol. Biol.}},
Doc-Delivery-Number = {{059SC}},
Unique-ID = {{ISI:000238751500002}},
}

@article{ ISI:000239478200010,
Author = {Nahar, Nazmun and Lyytinen, Kalle and Huda, Najmul and Muravyov, Sergey
   V.},
Title = {{Success factors for information technology supported international
   technology transfer: Finding expert consensus}},
Journal = {{INFORMATION \& MANAGEMENT}},
Year = {{2006}},
Volume = {{43}},
Number = {{5}},
Pages = {{663-677}},
Month = {{JUL}},
Abstract = {{Information technology (IT)-supported international technology transfer
   (ITT) is complex, risky, and fails often. No empirical studies are
   available on the factors that affect the success of IT-supported ITT. We
   review applicable theories (i.e. diffusion of innovation theory) and
   empirical research in conventional technology transfer to develop such a
   model. We carry out a multiple focus group method to rank factors that
   affect the success of IT-supported ITT and then apply a branch and bound
   method to derive a consensus ranking of these factors. The identified
   consensus ranking sheds light on factors that are similar to those of
   DOI theory and suggests a pattern of factors that affect IT-supported
   ITT. (c) 2006 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Nahar, N (Reprint Author), Univ Jyvaskyla, Dept Comp Sci \& Informat Syst, POB 35, FIN-40014 Jyvaskyla, Finland.
   Univ Jyvaskyla, Dept Comp Sci \& Informat Syst, FIN-40014 Jyvaskyla, Finland.
   Case Western Reserve Univ, Weatherhead Sch Management, Dept Informat Syst, Cleveland, OH 44106 USA.
   Tallinn Univ Technol, Dept Informat Proc, EE-0026 Tallinn, Estonia.
   Tomsk Polytech Univ, Dept Comp Aided measurement Syst \& Metrol, Tomsk 634050, Russia.}},
DOI = {{10.1016/j.im.2005.02.002}},
ISSN = {{0378-7206}},
EISSN = {{1872-7530}},
Keywords = {{success factors; IT support; IT implementation; international technology
   transfer; diffusion of innovation; consensus ranking}},
Keywords-Plus = {{ADOPTION; SYSTEMS}},
Research-Areas = {{Computer Science; Information Science \& Library Science; Business \&
   Economics}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Information Science \& Library
   Science; Management}},
Author-Email = {{naznaha@cc.jyu.fi}},
ResearcherID-Numbers = {{Muravyov, Sergey/N-2896-2013}},
ORCID-Numbers = {{Muravyov, Sergey/0000-0001-5650-1400}},
Cited-References = {{ALOBAIDI Z, 1999, HELSINKI SCH EC A, V151.
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Number-of-Cited-References = {{42}},
Times-Cited = {{15}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{Inf. Manage.}},
Doc-Delivery-Number = {{069VY}},
Unique-ID = {{ISI:000239478200010}},
}

@article{ ISI:000238869900016,
Author = {Schulz, E. and Karas, M. and Rosu, F. and Gabelica, V.},
Title = {{Influence of the matrix on analyte fragmentation in atmospheric pressure
   MALDI}},
Journal = {{JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY}},
Year = {{2006}},
Volume = {{17}},
Number = {{7}},
Pages = {{1005-1013}},
Month = {{JUL}},
Abstract = {{In this paper, we report the measurement of the degree of analyte
   fragmentation in AP-MALDI as a function of the matrix and of the laser
   fluence. The analytes include p-OCH3-benzylpyridinium, three peptides
   containing the sequence EEPP (which cleave very efficiently at the E-P
   site), and three deoxynucleosides (dA, dG, and dC), which lose the
   neutral sugar to give the protonated base. We found that the matrix
   hardness/softness was consistent when comparing the analytes, with a
   consensus ranking from hardest to softest: CHCA >> DHB > SA approximate
   to THAP > ATT > HPA. However, the exact ranking can be
   fluence-dependent, for example between ATT and HPA. Our goal here was to
   provide the scientific community with a detailed dataset that can be
   used to compare with theoretical predictions. We tried to correlate the
   consensus ranking with different matrix properties: sublimation or
   decomposition temperature (determined using thermogravimetry), analyte
   initial velocity, and matrix proton affinity. The best correlation was
   found with the matrix proton affinity.}},
Publisher = {{ELSEVIER SCIENCE INC}},
Address = {{360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Gabelica, V (Reprint Author), Univ Liege, Dept Chem, Mass Spectrometry Lab, Inst Chim, Bat B6C, B-4000 Liege, Belgium.
   Univ Liege, Dept Chem, Mass Spectrometry Lab, Inst Chim, B-4000 Liege, Belgium.
   Univ Frankfurt, Inst Pharmaceut Chem, D-6000 Frankfurt, Germany.}},
DOI = {{10.1016/j.jasms.2006.03.009}},
ISSN = {{1044-0305}},
Keywords-Plus = {{ASSISTED-LASER-DESORPTION/IONIZATION; INITIAL-ION VELOCITY; INTERNAL
   ENERGY; DESORPTION-IONIZATION; MASS-SPECTROMETRY;
   ELECTROSPRAY-IONIZATION; QUANTITATIVE MODEL; CALIBRATION; DEPENDENCE;
   MECHANISM}},
Research-Areas = {{Chemistry; Spectroscopy}},
Web-of-Science-Categories  = {{Chemistry, Analytical; Chemistry, Physical; Spectroscopy}},
Author-Email = {{v.gabelica@ulg.ac.be}},
ResearcherID-Numbers = {{Gabelica, Valerie/E-9417-2011
   Rosu, Frederic/E-6403-2011
   Fachbereich14, Dekanat/C-8553-2015}},
ORCID-Numbers = {{Gabelica, Valerie/0000-0001-9496-0165
   }},
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Number-of-Cited-References = {{34}},
Times-Cited = {{33}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{16}},
Journal-ISO = {{J. Am. Soc. Mass Spectrom.}},
Doc-Delivery-Number = {{061KC}},
Unique-ID = {{ISI:000238869900016}},
}

@article{ ISI:000233552400001,
Author = {Nuray, R and Can, F},
Title = {{Automatic ranking of information retrieval systems using data fusion}},
Journal = {{INFORMATION PROCESSING \& MANAGEMENT}},
Year = {{2006}},
Volume = {{42}},
Number = {{3}},
Pages = {{595-614}},
Month = {{MAY}},
Abstract = {{Measuring effectiveness of information retrieval (IR) systems is
   essential for research and development and for monitoring search quality
   in dynamic environments. In this study, we employ new methods for
   automatic ranking of retrieval systems. In these methods, we merge the
   retrieval results of multiple systems using various data fusion
   algorithms, use the top-ranked documents in the merged result as the
   ``(pseudo) relevant documents,{''} and employ these documents to
   evaluate and rank the systems. Experiments using Text REtrieval
   Conference (TREC) data provide statistically significant strong
   correlations with human-based assessments of the same systems. We
   hypothesize that the selection of systems that would return documents
   different from the majority could eliminate the ordinary systems from
   data fusion and provide better discrimination among the documents and
   systems. This could improve the effectiveness of automatic ranking.
   Based on this intuition, we introduce a new method for the selection of
   systems to be used for data fusion. For this purpose, we use the bias
   concept that measures the deviation of a system from the norm or
   majority and employ the systems with higher bias in the data fusion
   process. This approach provides even higher correlations with the
   human-based results. We demonstrate that our approach outperforms the
   previously proposed automatic ranking methods. (c) 2005 Elsevier Ltd.
   All rights reserved.}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Can, F (Reprint Author), Univ Calif Irvine, Sch Informat \& Comp Sci, Irvine, CA 92697 USA.
   Miami Univ, Dept Comp Sci \& Syst Anal, Oxford, OH 45056 USA.
   Bilkent Univ, Dept Comp Engn, TR-06800 Ankara, Turkey.}},
DOI = {{10.1016/j.ipm.2005.03.023}},
ISSN = {{0306-4573}},
Keywords = {{data fusion; experimentation; information retrieval; performance
   evaluation; rank aggregation}},
Keywords-Plus = {{WEB SEARCH; ENGINES}},
Research-Areas = {{Computer Science; Information Science \& Library Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Information Science \& Library
   Science}},
Author-Email = {{rabian@bilkent.edu.tr
   canf@muohio.edu}},
Cited-References = {{Amitay E., 2004, Proceedings of Sheffield SIGIR 2004. The Twenty-Seventh Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, DOI 10.1145/1008992.1008997.
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Number-of-Cited-References = {{31}},
Times-Cited = {{43}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{13}},
Journal-ISO = {{Inf. Process. Manage.}},
Doc-Delivery-Number = {{987XZ}},
Unique-ID = {{ISI:000233552400001}},
}

@article{ ISI:000234645400013,
Author = {Kengpol, A and Tuominen, M},
Title = {{A framework for group decision support systems: An application in the
   evaluation of information technology for logistics firms}},
Journal = {{INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS}},
Year = {{2006}},
Volume = {{101}},
Number = {{1}},
Pages = {{159-171}},
Month = {{MAY}},
Note = {{17th International Conference on Production Research, Virginia Polytech
   Inst \& State Univ, Blacksburg, VA, AUG, 2003}},
Abstract = {{The objective of this research is to propose a framework to enable
   decision-makers to achieve an overall consensus by using a group
   decision support system in the evaluation of information technology. The
   framework consists of a series of steps beginning with individual
   rankings of criteria by applying the analytic network process (ANP),
   through to a consensus ranking by utilising Delphi and Maximise
   Agreement Heuristic (MAH) methods. The contribution of this research
   ties in the methodology for integrating ANP, Delphi and MAH in order to
   perform quantitative and qualitative analysis in-depth to achieve the
   overall consensus ranking in association with a programme developed by
   the authors. The model assessment and its limitations using five
   logistics firms in Thailand are also presented. (c) 2005 Elsevier B.V.
   All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Kengpol, A (Reprint Author), King Mongkuts Inst Technol N Bangkok, Fac Engn, Dept Ind Engn, 1518 Piboolsongkram Rd, Bangkok 10800, Thailand.
   King Mongkuts Inst Technol N Bangkok, Fac Engn, Dept Ind Engn, Bangkok 10800, Thailand.
   Lappeenranta Univ Technol, Dept Ind Engn \& Management, FIN-53851 Lappeenranta, Finland.}},
DOI = {{10.1016/j.ijpe.2005.05.013}},
ISSN = {{0925-5273}},
Keywords = {{analytic network process; Delphi; Maximise Agreement Heuristic}},
Keywords-Plus = {{ANALYTIC NETWORK PROCESS; PROJECT SELECTION; CONSENSUS RANKING;
   MANAGEMENT; ALLOCATION; DESIGN}},
Research-Areas = {{Engineering; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Engineering, Industrial; Engineering, Manufacturing; Operations Research
   \& Management Science}},
Author-Email = {{athakorn@kmitnb.ac.th}},
Cited-References = {{DALKEY N, 1963, MANAGE SCI, V9, P458, DOI 10.1287/mnsc.9.3.458.
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Number-of-Cited-References = {{39}},
Times-Cited = {{28}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{12}},
Journal-ISO = {{Int. J. Prod. Econ.}},
Doc-Delivery-Number = {{002XM}},
Unique-ID = {{ISI:000234645400013}},
}

@inproceedings{ ISI:000238083200063,
Author = {Fernandez, Miriam and Vallet, David and Castells, Pablo},
Editor = {{Lalmas, M and MacFarlane, A and Ruger, S and Tombros, A and Tsikrika, T and Yavlinsky, A}},
Title = {{Probabilistic score normalization for rank aggregation}},
Booktitle = {{ADVANCES IN INFORMATION RETRIEVAL}},
Series = {{LECTURE NOTES IN COMPUTER SCIENCE}},
Year = {{2006}},
Volume = {{3936}},
Pages = {{553-556}},
Note = {{28th European Conference on Information Retrieval (ECIR 2006), Imperial
   Coll London, S Kensington, London, ENGLAND, APR   10, 2005-APR 12, 2006}},
Organization = {{Queen Mary Univ London; City Univ; Engn \& Phys Sci Res Council; CEPIS;
   Google; GCHQ; Microsoft Res; Yahoo Res; Sharp; Apriorie; Lemur
   Consulting; MMKM; Elsevier}},
Abstract = {{Rank aggregation is a pervading operation in IR technology. We
   hypothesize that the performance of score-based aggregation may be
   affected by artificial, usually meaningless deviations consistently
   occurring in the input score distributions, which distort the combined
   result when the individual biases differ from each other. We propose a
   score-based rank aggregation model where the source scores are
   normalized to a common distribution before being combined. Early
   experiments on available data from several TREC collections are shown to
   support our proposal.}},
Publisher = {{SPRINGER-VERLAG BERLIN}},
Address = {{HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Fernandez, M (Reprint Author), Univ Autonoma Madrid, Escuela Politecn Super, Ciudad Univ Cantoblanco, Madrid 28049, Spain.
   Univ Autonoma Madrid, Escuela Politecn Super, Madrid 28049, Spain.}},
ISSN = {{0302-9743}},
ISBN = {{3-540-33347-9}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Computer Science, Theory \&
   Methods}},
Author-Email = {{miriam.fernandez@uam.es
   david.vallet@uam.es
   pablo.castells@uam.es}},
ResearcherID-Numbers = {{Castells, Pablo/B-5020-2010
   Vallet, David/B-8332-2014}},
ORCID-Numbers = {{Castells, Pablo/0000-0003-0668-6317
   Vallet, David/0000-0002-0543-6730}},
Cited-References = {{Masthoff J, 2004, USER MODEL USER-ADAP, V14, P37, DOI 10.1023/B:USER.0000010138.79319.fd.
   CASTELLS P, 2005, LNCS, V3532, P455.
   Croft WB, 2000, ADV INFORMATION RETR, P1.
   LEE JH, 1997, 20 ANN INT ACM SIGIR, P267.
   MANMATHA R, 2001, 24 ANN INT ACM SIGIR, P267.
   MONTAGUE M, 2001, 10 C INF KNOWL MAN C, P427.
   RENDA ME, 2003, ACM S APPL COMP MELB, P841.}},
Number-of-Cited-References = {{7}},
Times-Cited = {{14}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{2}},
Doc-Delivery-Number = {{BEM01}},
Unique-ID = {{ISI:000238083200063}},
}

@inproceedings{ ISI:000235806300001,
Author = {Biedl, T and Brandenburg, FJ and Deng, XT},
Editor = {{Healy, P and Nikolov, NS}},
Title = {{Crossings and permutations}},
Booktitle = {{GRAPH DRAWING}},
Series = {{LECTURE NOTES IN COMPUTER SCIENCE}},
Year = {{2006}},
Volume = {{3843}},
Pages = {{1-12}},
Note = {{13th International Symposium on Graphy Drawing (GD 2005), Limerick,
   IRELAND, SEP 12-14, 2005}},
Organization = {{Sci Fdn Ireland; intel; Microsoft; Tom Sawyer Software; Natl ICT
   Australia; Enterprise Ireland; Failte Ireland; ILOG; Abslnt; DELL;
   JAMESON; Lucent Technol}},
Abstract = {{We investigate crossing minimization problems for a set of permutations,
   where a crossing expresses a disarrangement between elements. The goal
   is a common permutation pi{*} which minimizes the number of crossings.
   This is known as the Kemeny optimal aggregation problem minimizing the
   Kendall-tau distance. Recent interest into this problem comes from
   application to meta-search and spam reduction on the Web.
   This rank aggregation problem can be phrased as a one-sided two-layer
   crossing minimization problem for an edge coloured bipartite graph,
   where crossings are counted only for monochromatic edges.
   Here we introduce the max version of the crossing minimization problem,
   which attempts to minimize the discrimination against any permutation.
   We show the NP-hardness of the common and the max version for k >= 4
   permutations (and k even), and establish a 2-2/k and a 2-approximation,
   respectively. For two permutations crossing minimization is solved by
   inspecting the drawings, whereas it remains open for three permutations.}},
Publisher = {{SPRINGER-VERLAG BERLIN}},
Address = {{HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Biedl, T (Reprint Author), Univ Waterloo, Sch Comp Sci, Waterloo, ON N2L 3G1, Canada.
   Univ Waterloo, Sch Comp Sci, Waterloo, ON N2L 3G1, Canada.
   Univ Passau, Lehrstuhl Informat, D-94030 Passau, Germany.
   City Univ Hong Kong, Dept Comp Sci, Kowloon, Hong Kong, Peoples R China.}},
ISSN = {{0302-9743}},
ISBN = {{3-540-31425-3}},
Keywords-Plus = {{GRAPHS; ORDERS}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Software Engineering; Computer Science, Theory \&
   Methods}},
Author-Email = {{biedl@uwaterloo.ca
   brandenb@informatik.uni-passau.de
   csdeng@cityu.edu.hk}},
ResearcherID-Numbers = {{Deng, Xiaotie/E-8607-2011}},
ORCID-Numbers = {{Deng, Xiaotie/0000-0003-3189-5989}},
Cited-References = {{Ailon N., 2005, STOC, P684, DOI DOI 10.1145/1060590.1060692.
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Number-of-Cited-References = {{22}},
Times-Cited = {{9}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{1}},
Doc-Delivery-Number = {{BDW29}},
Unique-ID = {{ISI:000235806300001}},
}

@inproceedings{ ISI:000238574900026,
Author = {Straccia, Umberto and Troncy, Raphael},
Editor = {{Sure, Y and Domingue, J}},
Title = {{Towards distributed information retrieval in the Semantic Web: Query
   reformulation using the oMAP framework}},
Booktitle = {{SEMANTIC WEB: RESEARCH AND APPLICATIONS, PROCEEDINGS}},
Series = {{LECTURE NOTES IN COMPUTER SCIENCE}},
Year = {{2006}},
Volume = {{4011}},
Pages = {{378-392}},
Note = {{3rd European Semantic Web Conference, Budva, SERBIA MONTENEG, JUN 11-14,
   2006}},
Organization = {{Sekt; Dip; Knowledgeweb; Asg; Ontotext; iSOCO; Luisa; AKT; Oasis}},
Abstract = {{This paper introduces a general methodology for performing distributed
   search in the Semantic Web. We propose to define this task as a three
   steps process, namely resource selection, query reformulation/ontology
   alignment and rank aggregation/data fusion. For the second problem, we
   have implemented oMAP, a formal framework for automatically aligning OWL
   ontologies. In oMAP, different components are combined for finding
   suitable mapping candidates (together with their weights), and the set
   of rules with maximum matching probability is selected. Among these
   components, traditional terminological-based classifiers, machine
   learning-based classifiers and a new classifier using the structure and
   the semantics of the OWL ontologies; are proposed. oMAP has been
   evaluated on international test sets.}},
Publisher = {{SPRINGER-VERLAG BERLIN}},
Address = {{HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Straccia, U (Reprint Author), CNR, ISTI, Via G Moruzzi 1, I-56124 Pisa, Italy.
   CNR, ISTI, I-56124 Pisa, Italy.
   CWI Amsterdam, NL-1090 GB Amsterdam, Netherlands.}},
ISSN = {{0302-9743}},
ISBN = {{3-540-34544-2}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Computer Science, Theory \&
   Methods}},
Author-Email = {{straccia@isti.cnr.it
   raphael.troncy@cwi.n1}},
ResearcherID-Numbers = {{Lavbic, Dejan/G-1405-2010
   Straccia, Umberto/B-5373-2015
   }},
ORCID-Numbers = {{Lavbic, Dejan/0000-0003-2390-4160
   Straccia, Umberto/0000-0001-5998-6757
   Troncy, Raphael/0000-0003-0457-1436}},
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   Horrocks I., 2004, 13 INT WORLD WID WEB, P723.
   Horrocks I., 2003, J WEB SEMANT, V1, P7.
   Levenshtein V., 1966, SOV PHYS DOKL, V10, P707.
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   PORTER MF, 1980, PROGRAM-AUTOM LIBR, V14, P130, DOI 10.1108/eb046814.
   RENDA ME, 2003, 18 ANN ACM S APP COM, P841.
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   STOILOS G, 2005, 4 INT SEM WEB C ISWC, P624.
   STRACCIA U, 2005, 6 INT C WEB INF SYST, P133.
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   Winkler WE, 1999, INTERNAL REV SERVICE.
   YU C, 1999, 8 ACM CIKM C, P217.}},
Number-of-Cited-References = {{27}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{2}},
Doc-Delivery-Number = {{BEP50}},
Unique-ID = {{ISI:000238574900026}},
}

@article{ ISI:000228949100012,
Author = {Pauls, S and Aschoff, AJ and Wahl, J and Brambs, HJ and Fleiter, TR},
Title = {{Multi-detector row CT: Is prospective electrocardiographic triggering
   improving the detection of small pulmonary tumors?}},
Journal = {{ACADEMIC RADIOLOGY}},
Year = {{2005}},
Volume = {{12}},
Number = {{5}},
Pages = {{614-619}},
Month = {{MAY}},
Abstract = {{Rationale and Objectives. To compare prospectively ECG-triggered
   multi-detector row computed tomography (ECG-MDR-CT) and multi-detector
   row computed tomography (MDR-CT) without triggering for the detection of
   pulmonary tumors.
   Materials and Methods. 100 patients with proven or suspected tumors were
   referred for CT of the lung for staging of lung metastases. First, a
   non-enhanced scan was performed using prospective ECG-triggering on a
   four-row multidetector helical CT scanner, followed by a
   contrast-enhanced scan without triggering. The diagnostic assessibility
   in detecting intrapulmonary nodules and mediastinal structures was
   graded using a 5-point scale (rated 1 = bad to 5 = very good image
   quality).
   Results. ECG-MDR-CT images detected a total of 26\% more pulmonary
   nodules than MDR-CT. For tumors \&LT; 5 mm, the detection rate was 62\%
   higher using ECG-triggered scans (P =.024). Subjective assessment found
   median demarcation ratings for all pulmonary findings of 4 (ECG-MDR-CT)
   versus 3 (MDR-CT). Mediastinal structures were delineated better using
   ECG triggering. The median ranking for demarcation of pulmonary findings
   \&LT; 10 mm was 4 on ECG-MDR-CT and 3 on MDR-CT, respectively. For
   vessels and the left bronchus, the median of demarcation was 4 on
   triggered images and 2 on MDR-CT, respectively. The median values
   referring to the demarcation of mediastinal structures were not
   significantly different between ECG-MDR-CT and MDR-CT.
   Conclusion. Our data indicate the superiority of prospectively triggered
   ECG-MDR-CT over MDR-CT for the diagnosis of small pulmonary tumors using
   a 4-row multidetector CT. \&COPY; AUR, 2005.}},
Publisher = {{ASSOC UNIV RADIOLOGISTS}},
Address = {{820 JORIE BLVD, OAK BROOK, IL 60523-2251 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Pauls, S (Reprint Author), Univ Ulm, Dept Diagnost Radiol, Steinhoevelstr 9, D-89075 Ulm, Germany.
   Univ Ulm, Dept Diagnost Radiol, D-89075 Ulm, Germany.
   Univ Maryland Hosp, Dept Diagnost Imaging, Baltimore, MD USA.}},
DOI = {{10.1016/j.acra.2005.02.004}},
ISSN = {{1076-6332}},
Keywords = {{multi-detector row CT; ECG; pulmonary nodules}},
Keywords-Plus = {{THIN-SECTION CT; COMPUTED-TOMOGRAPHY; GANTRY ROTATION; SPIRAL CT; LUNG}},
Research-Areas = {{Radiology, Nuclear Medicine \& Medical Imaging}},
Web-of-Science-Categories  = {{Radiology, Nuclear Medicine \& Medical Imaging}},
Author-Email = {{sandra.pauls@medizin.uni-ulm.de}},
Cited-References = {{Schoepf UJ, 1999, RADIOLOGY, V212, P649.
   RITCHIE CJ, 1992, RADIOLOGY, V185, P37.
   Kachelriess M, 1998, MED PHYS, V25, P2417, DOI 10.1118/1.598453.
   Klingenbeck-Regn K, 1999, EUR J RADIOL, V31, P110, DOI 10.1016/S0720-048X(99)00086-8.
   Boese JM, 2000, RADIOLOGE, V40, P123, DOI 10.1007/s001170050020.
   Georg C, 2001, ROFO-FORTSCHR RONTG, V173, P536, DOI 10.1055/s-2001-14983.
   Mao S S, 1996, Am J Card Imaging, V10, P239.
   Montaudon M, 2001, EUR RADIOL, V11, P1681, DOI 10.1007/s003300000810.
   Mori K, 1998, J THORAC IMAG, V13, P211, DOI 10.1097/00005382-199807000-00009.
   Pauls S, 2003, ROFO-FORTSCHR RONTG, V175, P640, DOI 10.1055/s-2003-39208.
   Prokop M, 1996, RADIOLOGE, V36, P457, DOI 10.1007/s001170050098.
   Rubin GD, 1998, RADIOLOGY, V208, P771.
   VOCK P, 1990, RADIOLOGY, V176, P864.}},
Number-of-Cited-References = {{13}},
Times-Cited = {{2}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{1}},
Journal-ISO = {{Acad. Radiol.}},
Doc-Delivery-Number = {{923ZV}},
Unique-ID = {{ISI:000228949100012}},
}

@article{ ISI:000229232000010,
Author = {Cook, WD and Golany, B and Kress, M and Penn, M and Raviv, T},
Title = {{Optimal allocation of proposals to reviewers to facilitate effective
   ranking}},
Journal = {{MANAGEMENT SCIENCE}},
Year = {{2005}},
Volume = {{51}},
Number = {{4}},
Pages = {{655-661}},
Month = {{APR}},
Abstract = {{Peer review of research proposals and articles is an essential element
   in research and development processes worldwide. Here we consider a
   problem that, to the best of our knowledge, has not been addressed until
   now: how to assign subsets of proposals to reviewers in scenarios where
   the reviewers supply their evaluations through ordinal ranking. The
   solution approach we propose for this assignment problem maximizes the
   number of proposal pairs that will be evaluated by one or more
   reviewers. This new approach should facilitate meaningful aggregation of
   partial rankings of subsets of proposals by multiple reviewers into a
   consensus ranking. We offer two ways to implement the approach: an
   integer-programming set-covering model and a heuristic procedure. The
   effectiveness and efficiency of the two models are tested through an
   extensive simulation experiment.}},
Publisher = {{INST OPERATIONS RESEARCH  MANAGEMENT SCIENCES}},
Address = {{901 ELKRIDGE LANDING RD, STE 400, LINTHICUM HTS, MD 21090-2909 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Cook, WD (Reprint Author), York Univ, Schulich Sch Business, N York, ON M3J 1P3, Canada.
   York Univ, Schulich Sch Business, N York, ON M3J 1P3, Canada.
   Technion Israel Inst Technol, Fac Ind Engn \& Management, IL-32000 Haifa, Israel.
   Ctr Mil Anal, IL-31021 Haifa, Israel.
   USN, Postgrad Sch, Dept Operat Res, Monterey, CA 93943 USA.}},
DOI = {{10.1287/mnsc.1040.0290}},
ISSN = {{0025-1909}},
Keywords = {{peer review; ranking procedures; set covering}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
Author-Email = {{wcook@schulich.yorku.ca
   golany@ie.technion.ac.il
   mkress@ie.technion.ac.il
   mpenn@ie.technion.ac.il
   tal.raviv@sauder.ubc.ca}},
ResearcherID-Numbers = {{Raviv, Tal/K-4218-2012
   Raviv, Tal/K-2981-2013}},
ORCID-Numbers = {{Raviv, Tal/0000-0002-5960-2386
   Raviv, Tal/0000-0002-5960-2386}},
Cited-References = {{CICCHETTI DV, 1991, BEHAV BRAIN SCI, V14, P119.
   BOGART KP, 1975, SIAM J APPL MATH, V29, P254, DOI 10.1137/0129023.
   Langfeldt L, 2001, SOC STUD SCI, V31, P820, DOI 10.1177/030631201031006002.
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   KIRKWOOD CW, 1985, OPER RES, V33, P38, DOI 10.1287/opre.33.1.38.
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   Jayasinghe UW, 2001, EDUC EVAL POLICY AN, V23, P343, DOI 10.3102/01623737023004343.
   Cook W.D, 1978, MANAGE SCI, V24, P1721, DOI 10.1287/mnsc.24.16.1721.
   COOK WD, 1991, ORDINAL INFORMATION.
   Garg RK, 1996, J MARKET RES SOC, V38, P235.
   HODGSON C, 1995, CAN J CARDIOL, V11, P864.
   Kemeny J.G, 1962, MATH MODELS SOCIAL S, P9.}},
Number-of-Cited-References = {{12}},
Times-Cited = {{33}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{15}},
Journal-ISO = {{Manage. Sci.}},
Doc-Delivery-Number = {{927WU}},
Unique-ID = {{ISI:000229232000010}},
}

@inproceedings{ ISI:000231850500018,
Author = {Li, HG and Yu, HL and Agrawal, D and El Abbadi, A},
Editor = {{Tjoa, AM and Trujillo, J}},
Title = {{Progressive ranking of range aggregates}},
Booktitle = {{DATA WAREHOUSING AND KNOWLEDGE DISCOVERY, PROCEEDINGS}},
Series = {{Lecture Notes in Computer Science}},
Year = {{2005}},
Volume = {{3589}},
Pages = {{179-189}},
Note = {{7th International Conference on Data Warehousing and Knowledge Discovery
   (DaWaK 2005), Copenhagen, DENMARK, AUG 22-26, 2005}},
Abstract = {{Ranking-aware queries have been gaining much attention recently in many
   applications such as search engines and data streams. They are, however,
   not only restricted to such applications but are also very useful in
   OLAP applications. In this paper, we introduce aggregation ranking
   queries in OLAP data cubes motivated by an online advertisement tracking
   data warehouse application. These queries aggregate information over a
   specified range and then return the ranked order of the aggregated
   values. They differ from range aggregate queries in that range aggregate
   queries are mainly concerned with an aggregate operator such as SUM and
   MIN/MAX over the selected ranges of all dimensions in the data cubes.
   Existing techniques for range aggregate queries are not able to process
   aggregation ranking queries efficiently. Hence, in this paper we propose
   new algorithms to handle this problem. The essence of the proposed
   algorithms is based on both ranking and cumulative information to
   progressively rank aggregation results. Furthermore we empirically
   evaluate our techniques and the experimental results show that the query
   cost is improved significantly.}},
Publisher = {{SPRINGER-VERLAG BERLIN}},
Address = {{HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Li, HG (Reprint Author), Univ Calif Santa Barbara, Santa Barbara, CA 93106 USA.
   Univ Calif Santa Barbara, Santa Barbara, CA 93106 USA.}},
ISSN = {{0302-9743}},
ISBN = {{3-540-28558-X}},
Keywords-Plus = {{DATABASES; QUERIES}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Artificial Intelligence; Computer Science, Information
   Systems; Computer Science, Theory \& Methods}},
Author-Email = {{huagang@cs.ucsb.edu
   hailing@cs.ucsb.edu
   agrawal@cs.ucsb.edu
   amr@cs.ucsb.edu}},
Cited-References = {{Bruno N, 2002, PROC INT CONF DATA, P369, DOI 10.1109/ICDE.2002.994751.
   BABCOCK B, 2003, P INT C MAN DAT SIGM, P563.
   Bruno N, 2002, ACM T DATABASE SYST, V27, P153, DOI 10.1145/568518.568519.
   Chang K. C., 2002, P ACM SIGMOD INT C M, P346.
   Charikar M., 2002, P 29 INT C AUT LANG, P693.
   Donjerkovic D, 1999, PROCEEDINGS OF THE TWENTY-FIFTH INTERNATIONAL CONFERENCE ON VERY LARGE DATA BASES, P411.
   Fagin R., 1996, Proceedings of the Fifteenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. PODS 1996, DOI 10.1145/237661.237715.
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   Ho C.-T., 1997, P 1997 ACM SIGMOD IN, P73, DOI 10.1145/253260.253274.
   Ilyas I. F., 2002, Proceedings of the Twenty-eighth International Conference on Very Large Data Bases.
   Ilyas Ihab F., 2003, P 29 INT C VER LARG, P754, DOI 10.1016/B978-012722442-8/50072-0.
   LEE SY, 2000, P INT C VER LARG DAT, P232.
   LI C, 2005, P INT C MAN DAT SIGM.
   LI HG, 2004, RANKING AGGREGATES.}},
Number-of-Cited-References = {{15}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{1}},
Doc-Delivery-Number = {{BCY28}},
Unique-ID = {{ISI:000231850500018}},
}

@article{ ISI:000224235000006,
Author = {Chin, FYL and Deng, XT and Fang, QZ and Zhu, SF},
Title = {{Approximate and dynamic rank aggregation}},
Journal = {{THEORETICAL COMPUTER SCIENCE}},
Year = {{2004}},
Volume = {{325}},
Number = {{3}},
Pages = {{409-424}},
Month = {{OCT 6}},
Note = {{9th International Computing and Combinatorics Conference, Big Sky, MT,
   JUL 25-28, 2003}},
Abstract = {{Rank aggregation, originally an important issue in social choice theory,
   has become more and more important in information retrieval applications
   over the Internet, such as meta-search, recommendation system, etc. In
   this work, we consider an aggregation function using a weighted version
   of the normalized Kendall-tau distance. We propose a polynomial time
   approximation scheme, as well as a practical heuristic algorithm with
   the approximation ratio two for the NP-hard problem. In addition, we
   discuss issues and models for the dynamic rank aggregation problem. (C)
   2004 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Deng, XT (Reprint Author), City Univ Hong Kong, Dept Comp Sci, 83 Tat Chee Ave, Kowloon Tong, Hong Kong, Peoples R China.
   City Univ Hong Kong, Dept Comp Sci, Kowloon Tong, Hong Kong, Peoples R China.
   City Univ Hong Kong, Dept Comp Sci \& Informat Syst, Kowloon Tong, Hong Kong, Peoples R China.
   Ocean Univ China, Dept Math, Qingdao 266071, Peoples R China.}},
DOI = {{10.1016/j.tcs.2004.02.043}},
ISSN = {{0304-3975}},
Keywords = {{rank aggregation; Kendall-iota distance; coherence; weighted ECC}},
Keywords-Plus = {{ALGORITHMS; METASEARCH; ORDERS}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Theory \& Methods}},
Author-Email = {{chin@csis.hku.hk
   csdeng@cityu.edu.hk
   fangqizhi@public.qd.sd.cn
   zhusf@cs.cityu.edu.hk}},
ResearcherID-Numbers = {{Chin, Francis/C-1826-2009
   Deng, Xiaotie/E-8607-2011}},
ORCID-Numbers = {{Deng, Xiaotie/0000-0003-3189-5989}},
Cited-References = {{DIACONIS P, 1977, J ROY STAT SOC B MET, V39, P262.
   RAGHAVAN P, 1988, J COMPUT SYST SCI, V37, P130, DOI 10.1016/0022-0000(88)90003-7.
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   Charon I, 1997, DISCRETE MATH, V165, P139, DOI 10.1016/S0012-365X(96)00166-5.
   Dreilinger D, 1997, ACM T INFORM SYST, V15, P195, DOI 10.1145/256163.256164.
   DWORK C, 2001, P 10 INT C WORLD WID, V10, P613.
   Gauch S., 1996, J UNIVERS COMPUT SCI, V2, P637.
   Gillman D, 1998, SIAM J COMPUT, V27, P1203, DOI 10.1137/S0097539794268765.
   Karp R.M., 1972, COMPLEXITY COMPUTER, P85, DOI DOI 10.1007/978-1-4684-2001-2\_.
   WU Z, 2000, P 10 INT C WORLD WID, P386.
   Zhu SF, 2003, LECT NOTES COMPUT SC, V2690, P734.}},
Number-of-Cited-References = {{18}},
Times-Cited = {{8}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Theor. Comput. Sci.}},
Doc-Delivery-Number = {{859AT}},
Unique-ID = {{ISI:000224235000006}},
}

@article{ ISI:000223442300003,
Author = {George, J and Phun, YT and Bailey, MJ and Kong, DCM and Stewart, K},
Title = {{Development and validation of the medication regimen complexity index}},
Journal = {{ANNALS OF PHARMACOTHERAPY}},
Year = {{2004}},
Volume = {{38}},
Number = {{9}},
Pages = {{1369-1376}},
Month = {{SEP}},
Abstract = {{BACKGROUND: Medication regimen attributes, such as the number of drugs,
   dosage frequency, administration instructions, and the prescribed dosage
   forms, have been shown to influence patient outcomes. No single tool for
   quantifying the complexity of general medication regimens has been
   published in the medical literature.
   OBJECTIVE: To develop and validate a tool to quantify the complexity of
   prescribed medication regimens.
   METHODS: Literature findings and the expertise of the authors were used
   for developing the tool. Eight pharmacy researchers helped in
   establishing the tool's face and content validity. The new tool was
   tested on 134 medication regimens from patients with moderate to severe
   chronic obstructive pulmonary disease. Six regimens with a spread of
   scores on the tool were presented to a 5-member expert panel that
   subjectively ranked these regimens to confirm the tool's
   criterion-related validity. The relationships between scores on the tool
   and various independent variables were tested to judge the tool's
   construct validity. Two raters scored 25 regimens using the tool to test
   its inter-rater and test-retest reliabilities.
   RESULTS: A 65-item Medication Regimen Complexity Index (MRCI) was
   developed. The expert panel had strong agreement (Kendall's W = 0.8; p =
   0.001) on their individual rankings of the 6 regimens. The panel's
   consensus ranking had perfect correlation with the MRCI ranking. The
   total MRCI score had significant correlation with the number of drugs in
   the regimen (Spearman's Rho = 0.9; p < 0.0001), but not with the age and
   gender of the patients. Inter-rater and test-retest reliabilities for
   the total score and scores for individual sections on the MRCI were
   \&GE;0.9.
   CONCLUSIONS: The MRCI is a reliable and valid tool for quantifying drug
   regimen complexity with potential applications in both practice and
   research.}},
Publisher = {{HARVEY WHITNEY BOOKS CO}},
Address = {{PO BOX 42696, CINCINNATI, OH 45242 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Stewart, K (Reprint Author), Monash Univ, Victorian Coll Pharm, Dept Pharm Practice, 381 Royal Parade, Parkville, Vic 3052, Australia.
   Monash Univ, Victorian Coll Pharm, Dept Pharm Practice, Parkville, Vic 3052, Australia.
   Monash Univ, Fac Med, Dept Epidemiol \& Prevent Med, Clayton, Vic 3168, Australia.
   Alfred Hosp, Dept Pharm, Melbourne, Vic, Australia.}},
DOI = {{10.1345/aph.1D479}},
ISSN = {{1060-0280}},
Keywords = {{complexity; medication regimen index}},
Keywords-Plus = {{PATIENT CHARACTERISTICS; DOSAGE FREQUENCY; CONTROLLED TRIAL; ELDERLY
   PATIENTS; HOME; ADHERENCE; THERAPY; PRESCRIPTION; INTERVENTION; DISEASE}},
Research-Areas = {{Pharmacology \& Pharmacy}},
Web-of-Science-Categories  = {{Pharmacology \& Pharmacy}},
Author-Email = {{Kay.Stewart@vcp.monash.edu.au}},
ResearcherID-Numbers = {{Bailey, Michael /A-4499-2012}},
ORCID-Numbers = {{Bailey, Michael /0000-0002-5551-1401}},
Cited-References = {{Field TS, 2001, ARCH INTERN MED, V161, P1629, DOI 10.1001/archinte.161.13.1629.
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Number-of-Cited-References = {{27}},
Times-Cited = {{83}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{13}},
Journal-ISO = {{Ann. Pharmacother.}},
Doc-Delivery-Number = {{848BO}},
Unique-ID = {{ISI:000223442300003}},
}

@article{ ISI:000224641600002,
Author = {Ilyas, IF and Aref, WG and Elmagarmid, AK},
Title = {{Supporting top-k join queries in relational databases}},
Journal = {{VLDB JOURNAL}},
Year = {{2004}},
Volume = {{13}},
Number = {{3}},
Pages = {{207-221}},
Month = {{SEP}},
Note = {{29th Interantional Conference on Very Large Database, Berlin, GERMANY,
   2003}},
Abstract = {{Ranking queries, also known as top-k queries, produce results that are
   ordered on some computed score. Typically, these queries involve joins,
   where users are usually interested only in the top-k join results. Top-k
   queries are dominant in many emerging applications, e.g., multimedia
   retrieval by content, Web databases, data mining, middlewares, and most
   information retrieval applications. Current relational query processors
   do not handle ranking queries efficiently, especially when joins are
   involved. In this paper, we address supporting top-k join queries in
   relational query processors. We introduce a new rank-join algorithm that
   makes use of the individual orders of its inputs to produce join results
   ordered on a user-specified scoring function. The idea is to rank the
   join results progressively during the join operation. We introduce two
   physical query operators based on variants of ripple join that implement
   the rank-join algorithm. The operators are nonblocking and can be
   integrated into pipelined execution plans. We also propose an efficient
   heuristic designed to optimize a top-k join query by choosing the best
   join order. We address several practical issues and optimization
   heuristics to integrate the new join operators in practical query
   processors. We implement the new operators inside a prototype database
   engine based on PREDATOR. The experimental evaluation of our approach
   compares recent algorithms for joining ranked inputs and shows superior
   performance.}},
Publisher = {{SPRINGER}},
Address = {{233 SPRING STREET, NEW YORK, NY 10013 USA}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Ilyas, IF (Reprint Author), Univ Waterloo, Sch Comp Sci, Waterloo, ON N2L 3G1, Canada.
   Univ Waterloo, Sch Comp Sci, Waterloo, ON N2L 3G1, Canada.
   Purdue Univ, Dept Comp Sci, W Lafayette, IN 47907 USA.}},
DOI = {{10.1007/s00778-004-0128-2}},
ISSN = {{1066-8888}},
Keywords = {{ranking; top-k queries; rank aggregation; query operators}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Hardware \& Architecture; Computer Science,
   Information Systems}},
Author-Email = {{ilyas@uwaterloo.ca
   aref@cs.purdue.edu
   ake@cs.purdue.edu}},
ORCID-Numbers = {{Ilyas, Ihab/0000-0001-9052-9714}},
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Number-of-Cited-References = {{22}},
Times-Cited = {{42}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{1}},
Journal-ISO = {{VLDB J.}},
Doc-Delivery-Number = {{864OA}},
Unique-ID = {{ISI:000224641600002}},
}

@article{ ISI:000221608000002,
Author = {Verdonk, ML and Berdini, V and Hartshorn, MJ and Mooij, WTM and Murray,
   CW and Taylor, RD and Watson, P},
Title = {{Virtual screening using protein-ligand docking: Avoiding artificial
   enrichment}},
Journal = {{JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES}},
Year = {{2004}},
Volume = {{44}},
Number = {{3}},
Pages = {{793-806}},
Month = {{MAY-JUN}},
Abstract = {{This study addresses a number of topical issues around the use of
   protein-ligand docking in virtual screening. We show that, for the
   validation of such methods, it is key to use focused libraries
   (containing compounds with one-dimensional properties, similar to the
   actives), rather than ``random{''} or ``drug-like{''} libraries to test
   the actives against. We also show that, to obtain good enrichments, the
   docking program needs to produce reliable binding modes. We demonstrate
   how pharmacophores can be used to guide the dockings and improve
   enrichments, and we compare the performance of three consensus-ranking
   protocols against ranking based on individual scoring functions.
   Finally, we show that protein-ligand docking can be an effective aid in
   the screening for weak, fragment-like binders, which has rapidly become
   a popular strategy for hit identification. All results presented are
   based on carefully constructed virtual screening experiments against
   four targets, using the protein-ligand docking program GOLD.}},
Publisher = {{AMER CHEMICAL SOC}},
Address = {{1155 16TH ST, NW, WASHINGTON, DC 20036 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Verdonk, ML (Reprint Author), Astex Technol Ltd, 436 Cambridge Sci Pk,Milton Rd, Cambridge CB4 0QA, England.
   Astex Technol Ltd, Cambridge CB4 0QA, England.}},
DOI = {{10.1021/ci034289q}},
ISSN = {{0095-2338}},
Keywords-Plus = {{EMPIRICAL SCORING FUNCTIONS; MOLECULAR DOCKING; FLEXIBLE DOCKING;
   BINDING-AFFINITY; DRUG DISCOVERY; CHEMICAL DATABASES; GENETIC ALGORITHM;
   DATA-BANK; INHIBITORS; OPTIMIZATION}},
Research-Areas = {{Chemistry; Computer Science}},
Web-of-Science-Categories  = {{Chemistry, Multidisciplinary; Computer Science, Information Systems;
   Computer Science, Interdisciplinary Applications}},
Author-Email = {{m.verdonk@astex-technology.com}},
Cited-References = {{Hindle SA, 2002, J COMPUT AID MOL DES, V16, P129, DOI 10.1023/A:1016399411208.
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Number-of-Cited-References = {{52}},
Times-Cited = {{255}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{23}},
Journal-ISO = {{J. Chem. Inf. Comput. Sci.}},
Doc-Delivery-Number = {{823JQ}},
Unique-ID = {{ISI:000221608000002}},
}

@article{ ISI:000186883300007,
Author = {Lanning, DB and Nicholas, T and Palazotto, A},
Title = {{HCF notch predictions based on weakest-link failure models}},
Journal = {{INTERNATIONAL JOURNAL OF FATIGUE}},
Year = {{2003}},
Volume = {{25}},
Number = {{9-11}},
Pages = {{835-841}},
Month = {{SEP-NOV}},
Note = {{4th International Conference on Fatigue Damage of Structural Materials,
   HYANNIS, MASSACHUSETTS, SEP 22-27, 2002}},
Organization = {{USN; USA; USAF}},
Abstract = {{Weakest-link models for the prediction of the high cycle fatigue (HCF)
   limit stress of notched components were investigated. The models
   employed surface area elements in the high-stress region surrounding the
   root of a notch. Statistical descriptions of unnotched specimen
   experimental data were developed using Weibull distributions and median
   ranking, and incorporated into some of the weakest-link notch
   formulations. The predictions from each of the failure models were
   compared to the experimental 10(6) cycle fatigue limit stresses. The
   fatigue limit stresses were estimated using a step-loading technique at
   stress ratios from R = -1 to 0.8, for five geometries (elastic stress
   concentration factors of K-t = 2.0, 2.8 and 4.1) of circumferentially
   notched Ti-6Al-4V specimens. The methods were shown to be modestly
   successful, although data obtained at R = -1 and R > 0.65 could not be
   correlated well with data at intermediate values of R. (C) 2003 Elsevier
   Ltd. All rights reserved.}},
Publisher = {{ELSEVIER SCI LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Lanning, DB (Reprint Author), Embry Riddle Aeronaut Univ, Coll Engn, 3700 Willow Creek Rd, Prescott, AZ 86301 USA.
   Embry Riddle Aeronaut Univ, Coll Engn, Prescott, AZ 86301 USA.
   AFIT, ENY, Wright Patterson AFB, OH 45433 USA.}},
DOI = {{10.1016/S0142-1123(03)00156-7}},
ISSN = {{0142-1123}},
Keywords = {{high cycle fatigue; notches; Ti-6Al-4V; weakest link; Weibull
   distribution}},
Keywords-Plus = {{TI-6AL-4V; SPECIMENS}},
Research-Areas = {{Engineering; Materials Science}},
Web-of-Science-Categories  = {{Engineering, Mechanical; Materials Science, Multidisciplinary}},
Cited-References = {{Lanning DB, 1999, INT J FATIGUE, V21, pS87.
   Bellows RS, 1999, INT J FATIGUE, V21, P687, DOI 10.1016/S0142-1123(99)00032-8.
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   Neuber H., 1946, THEORY NOTCH STRESSE.
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   WEIBULL W, 1951, J APPL MECH-T ASME, V18, P293.}},
Number-of-Cited-References = {{13}},
Times-Cited = {{14}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{Int. J. Fatigue}},
Doc-Delivery-Number = {{748WD}},
Unique-ID = {{ISI:000186883300007}},
}

@article{ ISI:000182030100002,
Author = {Leyva-Lopez, JC and Fernandez-Gonzalez, E},
Title = {{A new method for group decision support based on ELECTRE III methodology}},
Journal = {{EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}},
Year = {{2003}},
Volume = {{148}},
Number = {{1}},
Pages = {{14-27}},
Month = {{JUL 1}},
Abstract = {{Group decision is usually understood as the reduction of different
   individual preferences on a given set to a single collective preference.
   At present. there are few approaches which solve the group ranking
   problem with multiple criteria in a widely acceptable way. Often, they
   rest on a poor heuristic which makes it decision about consensus ranking
   difficult to support. This paper presents an extension of the ELECTRE
   III multicriteria outranking methodology to assist a group of decision
   makers with different value systems to achieve a consensus on a set of
   possible alternatives, Our proposal starts with N individual rankings
   and N corresponding valued preference functions, and uses the natural
   heuristic provided by ELECTRE methodology for obtaining it fuzzy binary
   relation representing the collective preference. A comparison of this
   method with PROMETHEE 11 for group decision is carried out. We found
   that, in this particular application. the proposed heuristic based on
   majority rules combined with concessions to significant minorities.
   performs relatively better than a compensatory scheme based on it net
   flow weighted SLIM function. (C) 2002 Elsevier Science B.V. All rights
   reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Leyva-Lopez, JC (Reprint Author), Univ Autonoma Sinaloa, Fac Ingn, Ciudad Univ,Calzada Las Amer S-N,, Mexico City 80040, DF, Mexico.
   Univ Autonoma Sinaloa, Fac Ingn, Mexico City 80040, DF, Mexico.}},
DOI = {{10.1016/S0377-2217(02)00273-4}},
ISSN = {{0377-2217}},
EISSN = {{1872-6860}},
Keywords = {{multicriteria analysis; group decision; outranking methods; ELECTRE III;
   genetic algorithms}},
Keywords-Plus = {{MULTICRITERIA}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
Author-Email = {{jleyva@uas.uasnet.mx
   eddyf@uas.uasnet.mx}},
Cited-References = {{Hokkanen J, 1997, EUR J OPER RES, V98, P19, DOI 10.1016/0377-2217(95)00325-8.
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Number-of-Cited-References = {{22}},
Times-Cited = {{65}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{14}},
Journal-ISO = {{Eur. J. Oper. Res.}},
Doc-Delivery-Number = {{663WR}},
Unique-ID = {{ISI:000182030100002}},
}

@article{ ISI:000183825700004,
Author = {Tavana, M},
Title = {{CROSS: A multicriteria group-decision-making model for evaluating and
   prioritizing advanced-technology projects at NASA}},
Journal = {{INTERFACES}},
Year = {{2003}},
Volume = {{33}},
Number = {{3}},
Pages = {{40-56}},
Month = {{MAY-JUN}},
Abstract = {{Evaluating and prioritizing advanced-technology projects is a
   particularly difficult task for the staff at the Kennedy Space Center
   (KSC) shuttle project engineering office. Because the evaluation process
   is complex and unstructured, decision makers (DMs) must consider vast
   amounts of diverse information concerning safety, systems engineering,
   cost savings, process enhancement, reliability, and implementation.
   Intuitive methods developed in the past have helped them to use large
   volumes of information in evaluating projects. However, these intuitive
   methods do not provide a structured framework for systematic evaluation.
   CROSS (consensus-ranking organizational-support system) is a
   multicriteria group-decision-making model that I implemented
   successfully at KSC to capture the DMs' beliefs through sequential,
   rational, and analytical processes. CROSS uses the analytic hierarchy
   process (AHP), subjective probabilities, the entropy concept, and the
   maximize-agreement heuristic (MAH) to enhance the DMs' intuition in
   evaluating sets of projects.}},
Publisher = {{INST OPERATIONS RESEARCH  MANAGEMENT SCIENCES}},
Address = {{901 ELKRIDGE LANDING RD, STE 400, LINTHICUM HTS, MD 21090-2909 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Tavana, M (Reprint Author), La Salle Univ, Dept Management, Philadelphia, PA 19141 USA.
   La Salle Univ, Dept Management, Philadelphia, PA 19141 USA.}},
DOI = {{10.1287/inte.33.3.40.16014}},
ISSN = {{0092-2102}},
Keywords = {{government : programs; decision analysis : multiple criteria}},
Keywords-Plus = {{ANALYTIC HIERARCHY PROCESS; RESEARCH-AND-DEVELOPMENT; SELECTION; SYSTEM;
   METHODOLOGY; AHP; PROBABILITIES; ALLOCATION; FRAMEWORK; PHRASES}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
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Number-of-Cited-References = {{53}},
Times-Cited = {{18}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{9}},
Journal-ISO = {{Interfaces}},
Doc-Delivery-Number = {{695HU}},
Unique-ID = {{ISI:000183825700004}},
}

@article{ ISI:000184718600001,
Author = {Beg, MMS and Ahmad, N},
Title = {{Soft computing techniques for rank aggregation on the World Wide Web}},
Journal = {{WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS}},
Year = {{2003}},
Volume = {{6}},
Number = {{1}},
Pages = {{5-22}},
Month = {{MAR}},
Abstract = {{Rank aggregation is the problem of generating a near-{''}consensus{''}
   ranking for a given set of rankings. When applied to the web, this finds
   applications in meta-searching, search engine comparison, spam fighting
   and word association techniques. The rank aggregation obtained by
   optimizing the Spearman footrule distance is called footrule optimal
   aggregation (FOA), and it also satisfies the Condorcet property. We find
   in literature a polynomial time algorithm to compute FOA for full lists.
   However, when collating the results of the search engines, the lists are
   almost invariably always the partial ones, as different search engines
   usually return non-overlapping lists of documents. The FOA for partial
   lists, however, is NP-hard. This NP-hard nature of partial footrule
   optimal aggregation problem (PFOA) motivates us to apply genetic
   algorithm (GA) for the PFOA problem. The GA based technique may take
   long to compute, but we propose to decide upon the number of generations
   of GA based on the time limit allowed by the user. We have also
   considered some ``positional{''} methods, as they are linear in
   complexity. A classical positional method is the Borda's methods Since,
   fuzzy logic has been extensively studied in literature for arriving at
   consensus in group decision making, the adoption of some fuzzy
   techniques is also being investigated here for getting an improvement
   over the Borda's method. We have not only adopted and compared the
   classical fuzzy rank ordering techniques for web applications, but also
   proposed three novel techniques that outshine the existing techniques.}},
Publisher = {{KLUWER ACADEMIC PUBL}},
Address = {{VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ahmad, N (Reprint Author), Indian Inst Technol, Dept Elect Engn, New Delhi 110016, India.
   Indian Inst Technol, Dept Elect Engn, New Delhi 110016, India.}},
DOI = {{10.1023/A:1022344031752}},
ISSN = {{1386-145X}},
Keywords = {{World Wide Web; rank aggregation; genetic algorithm; fuzzy ordering;
   meta-searching}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Computer Science, Software
   Engineering}},
Cited-References = {{Ahmad N., 2002, P INT C ART INT ENG, P363.
   DIACONIS P, 1977, J ROY STAT SOC B MET, V39, P262.
   FORREST S, 1993, SCIENCE, V261, P872, DOI 10.1126/science.8346439.
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   Ross T. J., 1997, FUZZY LOGIC ENG APPL.
   SHIMURA M, 1973, MATH ANAL APPL, V43, P717.}},
Number-of-Cited-References = {{12}},
Times-Cited = {{18}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{World Wide Web}},
Doc-Delivery-Number = {{711BN}},
Unique-ID = {{ISI:000184718600001}},
}

@inproceedings{ ISI:000185044800028,
Author = {Deng, XT and Fang, QZ and Zhu, SF},
Editor = {{Warnow, T and Zhu, B}},
Title = {{Approximate rank aggregation (Preliminary version)}},
Booktitle = {{COMPUTING AND COMBINATORICS, PROCEEDINGS}},
Series = {{LECTURE NOTES IN COMPUTER SCIENCE}},
Year = {{2003}},
Volume = {{2697}},
Pages = {{262-271}},
Note = {{9th Annual International Conference on Computing and Combinatorics, BIG
   SKY, MONTANA, JUL 25-28, 2003}},
Organization = {{Montana State Univ, Comp Sci Dept}},
Abstract = {{In this paper, we consider algorithmic issues of the rank aggregation
   problem for information retrieval on the Web. We introduce a weighted
   version of the metric of the normalized Kendall-tau distance, originally
   proposed for the problem by Dwork, et al.,{[}7] and show that it
   satisfies the extended Condorcet criterion. Our main technical
   contribution is a polynomial time approximation scheme, in addition to a
   practical heuristic algorithm with ratio 2 for the NP-hard problem.}},
Publisher = {{SPRINGER-VERLAG BERLIN}},
Address = {{HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Deng, XT (Reprint Author), City Univ Hong Kong, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China.
   City Univ Hong Kong, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China.
   Ocean Univ Qingdao, Dept Math, Qingdao 266071, Peoples R China.}},
ISSN = {{0302-9743}},
ISBN = {{3-540-40534-8}},
Keywords = {{rank aggregation; Kendall-tau distance; coherence; weighted ECC}},
Keywords-Plus = {{ALGORITHMS; ORDERS}},
Research-Areas = {{Computer Science; Mathematics}},
Web-of-Science-Categories  = {{Computer Science, Theory \& Methods; Mathematics, Applied}},
ResearcherID-Numbers = {{Deng, Xiaotie/E-8607-2011}},
ORCID-Numbers = {{Deng, Xiaotie/0000-0003-3189-5989}},
Cited-References = {{RAGHAVAN P, 1988, J COMPUT SYST SCI, V37, P130, DOI 10.1016/0022-0000(88)90003-7.
   RAGHAVAN P, 1987, COMBINATORICA, V7, P365, DOI 10.1007/BF02579324.
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   DWORK C, 2001, RANK AGGREGATION MET, V10, P613.
   Gillman D, 1998, SIAM J COMPUT, V27, P1203, DOI 10.1137/S0097539794268765.
   Karp R.M., 1972, COMPLEXITY COMPUTER, P85, DOI DOI 10.1007/978-1-4684-2001-2\_.}},
Number-of-Cited-References = {{12}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{1}},
Doc-Delivery-Number = {{BX35M}},
Unique-ID = {{ISI:000185044800028}},
}

@article{ ISI:000186767100009,
Author = {Fagin, R and Kumar, R and Sivakumar, D},
Title = {{Comparing top k lists}},
Journal = {{SIAM JOURNAL ON DISCRETE MATHEMATICS}},
Year = {{2003}},
Volume = {{17}},
Number = {{1}},
Pages = {{134-160}},
Abstract = {{Motivated by several applications, we introduce various distance
   measures between ``top k lists.{''} Some of these distance measures are
   metrics, while others are not. For each of these latter distance
   measures, we show that they are ``almost{''} a metric in the following
   two seemingly unrelated aspects:
   (i) they satisfy a relaxed version of the polygonal ( hence, triangle)
   inequality, and
   (ii) there is a metric with positive constant multiples that bound our
   measure above and below.
   This is not a coincidence - we show that these two notions of almost
   being a metric are the same. Based on the second notion, we de. ne two
   distance measures to be equivalent if they are bounded above and below
   by constant multiples of each other. We thereby identify a large and
   robust equivalence class of distance measures.
   Besides the applications to the task of identifying good notions of
   (dis) similarity between two top k lists, our results imply
   polynomial-time constant-factor approximation algorithms for the rank
   aggregation problem with respect to a large class of distance measures.}},
Publisher = {{SIAM PUBLICATIONS}},
Address = {{3600 UNIV CITY SCIENCE CENTER, PHILADELPHIA, PA 19104-2688 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Fagin, R (Reprint Author), IBM Corp, Almaden Res Ctr, 650 Harry Rd, San Jose, CA 95120 USA.
   IBM Corp, Almaden Res Ctr, San Jose, CA 95120 USA.}},
DOI = {{10.1137/S0895480102412856}},
ISSN = {{0895-4801}},
EISSN = {{1095-7146}},
Keywords = {{triangle inequality; polygonal inequality; metric; near metric; distance
   measures; top k list; rank aggregation}},
Keywords-Plus = {{PERFORMANCE GUARANTEES; TRIANGLE INEQUALITY}},
Research-Areas = {{Mathematics}},
Web-of-Science-Categories  = {{Mathematics, Applied}},
Author-Email = {{fagin@almaden.ibm.com
   ravi@almaden.ibm.com
   siva@almaden.ibm.com}},
Cited-References = {{Fagin R, 1998, INT J COMPUT VISION, V30, P219, DOI 10.1023/A:1008023416823.
   ANDREAE T, 1995, SIAM J DISCRETE MATH, V8, P1, DOI 10.1137/S0895480192240226.
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   LEE JH, 1997, DATABASE SYSTEMS ADV, P421, DOI 10.1142/9789812819536\_0044.}},
Number-of-Cited-References = {{16}},
Times-Cited = {{147}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{SIAM Discret. Math.}},
Doc-Delivery-Number = {{746UY}},
Unique-ID = {{ISI:000186767100009}},
}

@article{ ISI:000178416400003,
Author = {Welsford, M and Morrison, LJ},
Title = {{Defining the outcome measures for out-of-hospital trials in acute
   pulmonary edema}},
Journal = {{ACADEMIC EMERGENCY MEDICINE}},
Year = {{2002}},
Volume = {{9}},
Number = {{10}},
Pages = {{983-988}},
Month = {{OCT}},
Note = {{Annual Meeting of the National-Association-of-Emergency-Medical-Services
   (EMS), DANA POINT, CALIFORNIA, JAN, 2000}},
Organization = {{Natl Assoc Emergency Med Serv}},
Abstract = {{Objective: Comparing studies of the effectiveness of out-of-hospital
   interventions in acute pulmonary edema (APE) is difficult due to the
   diversity of outcome measures used in the literature. The objective of
   this study was to define a set of clinically relevant outcome measures
   for future out-of-hospital trials in APE. Methods: A Medline search and
   hand-search of bibliographies was undertaken to develop a list of APE
   outcome measures. A survey was mailed to a sample of 227 Canadian
   emergency physicians using the Dillman methodology, requesting that
   respondents select clinically relevant outcome measures from this list
   and rank them by importance. A selection frequency of greater than or
   equal to 70\% and a median ranking score were used to determine relevant
   outcome measures. Results: The Medline and bibliography search
   identified 21 APE outcome measures. The survey response rate was 71\%.
   Outcome measures selected most frequently were heart rate, respiratory
   rate, respiratory distress scale, subjective dyspnea scale,
   out-of-hospital intubation, emergency department (ED) intubation,
   survival to discharge, and out-of-hospital mortality. The median ranking
   score identified a similar set of measures: heart rate, respiratory
   rate, respiratory distress scale, subjective dyspnea scale,
   out-of-hospital intubation rate, and ED intubation rate. There was no
   significant difference in outcome selection between physicians who
   worked in communities with and without advanced out-of-hospital care.
   Conclusions: Clinically relevant out-of-hospital APE outcome measures
   were identified and endorsed by a representative survey of Canadian
   emergency physicians. Clinicians appear to favor short-term and
   non-mortality outcomes for out-of-hospital interventions. The use of
   this set of APE outcome measures may improve the design and
   comparability of future out-of-hospital trials.}},
Publisher = {{HANLEY \& BELFUS INC}},
Address = {{210 S 13TH ST, PHILADELPHIA, PA 19107 USA}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Morrison, LJ (Reprint Author), Univ Toronto, Ctr Hlth Sci, Prehosp Res Program, Sunnybrook \& Womens Coll, Room BG20,2075 Bayview Ave, Toronto, ON M4N 3M5, Canada.
   Univ Toronto, Ctr Hlth Sci, Prehosp Res Program, Sunnybrook \& Womens Coll, Toronto, ON M4N 3M5, Canada.
   Univ Toronto, Div Emergency Med, Dept Med, Toronto, ON, Canada.
   Toronto Emergency Med Serv, Toronto, ON, Canada.}},
DOI = {{10.1111/j.1553-2712.2002.tb02129.x}},
ISSN = {{1069-6563}},
Keywords = {{pulmonary edema; heart failure; congestive; emergency medical services;
   emergency treatment; treatment outcome; survey methodology}},
Keywords-Plus = {{POSITIVE AIRWAY PRESSURE; CONGESTIVE-HEART-FAILURE; EMERGENCY TREATMENT;
   CARDIOGENIC-SHOCK; ED MANAGEMENT; NITROGLYCERIN; THERAPY; NITRATES;
   MORPHINE; SAFETY}},
Research-Areas = {{Emergency Medicine}},
Web-of-Science-Categories  = {{Emergency Medicine}},
ResearcherID-Numbers = {{morrison, laurie/A-6325-2012
   }},
ORCID-Numbers = {{morrison, laurie/0000-0001-8369-9774
   Welsford, Michelle/0000-0003-2682-641X}},
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Number-of-Cited-References = {{42}},
Times-Cited = {{5}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{Acad. Emerg. Med.}},
Doc-Delivery-Number = {{600XE}},
Unique-ID = {{ISI:000178416400003}},
}

@article{ ISI:000172083200014,
Author = {Prasad, RS},
Title = {{Development of the HIV/AIDS Q-Sort instrument to measure physician
   attitudes}},
Journal = {{FAMILY MEDICINE}},
Year = {{2001}},
Volume = {{33}},
Number = {{10}},
Pages = {{772-778}},
Month = {{NOV-DEC}},
Abstract = {{Background: Providers' attitudes about HIV/AIDS are an important
   dimension in the delivery of quality care to persons with HIV/AIDS. It
   is believed that education can alter attitudes, but there is a need for
   a user-friendly instrument to measure the effect that HIV/AIDS
   educational programs have on attitudes. Methods: A pool of HIV/AIDS
   attitude descriptors was collected through literature review and from
   individuals working in the HIV/AIDS field. Out of this pool of 90
   descriptors, 48 descriptors with the highest face validity were selected
   through expert consensus ranking to create a preliminary survey
   instrument. Twenty-six physicians completed a pilot Q-Sort instrument
   with 48 descriptors. A variance analysis was conducted, and the top 28
   descriptors with the most variability were selected for the final Q-Sort
   instrument, which was then completed by 191 physicians. A factor
   analysis was conducted to identify a small number of factors that
   explained the 28 descriptors. A subsample of 22 physicians repeated the
   test to establish test-retest reliability. Results: Factor analysis
   revealed three factors: (1) emotionality, (2) ability, and (3)
   reluctance. The Q-Sort instrument demonstrated good test-retest
   reliability, with reliability for the three factors of .82, .80, and
   .88, respectively. Conclusions: This Q-sort instrument is a reliable
   method for measuring physician attitudes toward HIV/AIDS patients.
   Further studies can test its use for evaluating the effect of
   educational programs on changing provider attitudes.}},
Publisher = {{SOC TEACHERS FAMILY MEDICINE}},
Address = {{11400 TOMAHAWK CREEK PARKWAY, STE 540, LEAWOOD, KS 66207 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Prasad, RS (Reprint Author), Univ So Calif, Dept Family Med, 1420 San Pablo St,PMB-B205, Los Angeles, CA 90033 USA.
   Univ So Calif, Dept Family Med, Los Angeles, CA 90033 USA.}},
ISSN = {{0742-3225}},
Keywords-Plus = {{MEDICAL-EDUCATION; AIDS; SCALE; HEALTH; DIMENSIONS; ATTACHMENT;
   STUDENTS; FEAR}},
Research-Areas = {{General \& Internal Medicine}},
Web-of-Science-Categories  = {{Primary Health Care; Medicine, General \& Internal}},
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   1993, INT C AIDS JUN 6 11, V9, P775.}},
Number-of-Cited-References = {{35}},
Times-Cited = {{13}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Fam. Med.}},
Doc-Delivery-Number = {{490ZH}},
Unique-ID = {{ISI:000172083200014}},
}

@article{ ISI:000169073800003,
Author = {Yacavone, RF and Locke, GR and Gostout, CJ and Rockwood, TH and
   Thieling, S and Zinsmeister, AR},
Title = {{Factors influencing patient satisfaction with GI endoscopy}},
Journal = {{GASTROINTESTINAL ENDOSCOPY}},
Year = {{2001}},
Volume = {{53}},
Number = {{7}},
Pages = {{703-710}},
Month = {{JUN}},
Note = {{Digestive Disease Week/101st Annual Meeting of the
   American-Gastroenterological-Association, SAN DIEGO, CALIFORNIA, MAY
   21-24, 2000}},
Organization = {{Amer Gastroenterol Assoc}},
Abstract = {{Background: A modified Group Health Association of America-9 survey
   (mGHAA-9) was recently proposed for measurement of patient satisfaction
   with endoscopy. It is unknown whether the mGHAA-9 addresses the issues
   most important to this outcome.
   Methods: A 15-item survey of factors potentially important to patient
   satisfaction with endoscopy was developed, including the 6 core mGHAA-9
   items. Respondents were asked to rank the factors from 1 to 15 (1 = most
   important to 15 = least important to satisfaction). Two groups were
   surveyed: 1(1) patients with prior endoscopy experience and (2)
   physician endoscopists. Item rank distributions overall and by patient
   age, gender, and procedure experience were examined.
   Results: Of 559 outpatients surveyed, 437 (78\%) provided complete
   responses. The mean patient;sge was 59 years (48.7\% female, 45.3\%
   male, 6\% not stated). The number 1 ranked factor was the endoscopist's
   technical skills (median ranking (mr)= 1), an item included in the
   mGHAA-9. Pain control, a factor not assessed by the mGHAA-9, was second
   (mr = 4), and ranked number 7 by 16\% of patients. Item rankings were
   consistent across patient subgroups. Relative to patients, endoscopists
   underprioritized preprocedure and postprocedure communication.
   Conclusions: The mGHAA-9 has inadequate content validity for measurement
   of patient satisfaction with endoscopy because it does not assess pain
   control. However, endoscopy satisfaction measurement with a single,
   universally applied instrument appears feasible.}},
Publisher = {{MOSBY, INC}},
Address = {{11830 WESTLINE INDUSTRIAL DR, ST LOUIS, MO 63146-3318 USA}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Locke, GR (Reprint Author), Mayo Clin \& Mayo Fdn, Gastroenterol \& Hepatol Outcomes Res Unit, W 19A Mayo Bldg,200 1st St SW, Rochester, MN 55905 USA.
   Mayo Clin \& Mayo Fdn, Gastroenterol \& Hepatol Outcomes Res Unit, Rochester, MN 55905 USA.
   Mayo Clin \& Mayo Fdn, Biostat Sect, Rochester, MN 55905 USA.
   Univ Minnesota, Sch Publ Hlth, Div Hlth Serv Res \& Policy, Minneapolis, MN USA.}},
DOI = {{10.1067/mge.2001.115337}},
ISSN = {{0016-5107}},
Keywords-Plus = {{UPPER GASTROINTESTINAL ENDOSCOPY; ORAL SODIUM-PHOSPHATE; CONSCIOUS
   SEDATION; COLONOSCOPY; PREMEDICATION}},
Research-Areas = {{Gastroenterology \& Hepatology}},
Web-of-Science-Categories  = {{Gastroenterology \& Hepatology}},
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Number-of-Cited-References = {{20}},
Times-Cited = {{59}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Gastrointest. Endosc.}},
Doc-Delivery-Number = {{438UZ}},
Unique-ID = {{ISI:000169073800003}},
}

@article{ ISI:000166759700016,
Author = {Trifonov, EN},
Title = {{Consensus temporal order of amino acids and evolution of the triplet
   code}},
Journal = {{GENE}},
Year = {{2000}},
Volume = {{261}},
Number = {{1}},
Pages = {{139-151}},
Month = {{DEC 30}},
Note = {{Anton Dohrn Workshop on Neutralism and Selectionism - the End of a
   Debate, ISCHIA, ITALY, MAY 03-05, 2000}},
Organization = {{Int Soc Molec Evolut}},
Abstract = {{Forty different single-factor criteria and multi-factor hypotheses about
   chronological order of appearance of amino acids in the early evolution
   are summarized in consensus ranking. All available knowledge and
   thoughts about origin and evolution of the genetic code are thus
   combined in a single list where the amino acids are ranked
   chronologically. Due to consensus nature of the chronology it has
   several important properties not visible in individual rankings by any
   of the initial criteria. Nine amino acids of the Miller's imitation of
   primordial environment are all ranked as topmost (G, A, V, D, E, P, S,
   L, T). This result does not change even after several criteria related
   to Miller's data are excluded from calculations. The consensus order of
   appearance of the 20 amino acids on the evolutionary scene also reveals
   a unique and strikingly simple chronological organization of 64 codons,
   that could not be figured out from individual criteria: New codons
   appear in descending order of their thermostability, as complementary
   pairs, with the complements recruited sequentially from the codon
   repertoires of the earlier or simultaneously appearing amino acids.
   These three rules (Thermostability, Complementarity and Processivity)
   hold strictly as well as leading position of the earliest amino acids
   according to Miller. The consensus chronology of amino acids, G/A, V/D,
   P, S, E/L, T, R, N, K, Q, I, C, H, F, M, Y, W, and the derived temporal
   order for codons may serve, thus, as a justified working model of choice
   for further studies on the origin and evolution of the genetic code. (C)
   2000 Elsevier Science B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Trifonov, EN (Reprint Author), Weizmann Inst Sci, Dept Struct Biol, IL-76100 Rehovot, Israel.
   Weizmann Inst Sci, Dept Struct Biol, IL-76100 Rehovot, Israel.}},
DOI = {{10.1016/S0378-1119(00)00476-5}},
ISSN = {{0378-1119}},
Keywords = {{abiotic; chronology of amino acids; chronology of codons; origin of
   life; origin of code}},
Keywords-Plus = {{GENETIC-CODE; TRANSFER-RNAS; ORIGIN; PROTEINS; COEVOLUTION; COMPLEXITY;
   BLOCKS; CODONS; MODEL; PAIRS}},
Research-Areas = {{Genetics \& Heredity}},
Web-of-Science-Categories  = {{Genetics \& Heredity}},
Cited-References = {{ALTSHTEIN AD, 1988, MOL BIOL+, V22, P1133.
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Number-of-Cited-References = {{50}},
Times-Cited = {{104}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{8}},
Journal-ISO = {{Gene}},
Doc-Delivery-Number = {{398MF}},
Unique-ID = {{ISI:000166759700016}},
}

@article{ ISI:000086265800014,
Author = {Tripathi, GP},
Title = {{Weighted generalised directed-divergence measure to assess military
   requirements}},
Journal = {{DEFENCE SCIENCE JOURNAL}},
Year = {{2000}},
Volume = {{50}},
Number = {{1}},
Pages = {{101-106}},
Month = {{JAN}},
Abstract = {{In the present paper, a weighted information theoretic measure has been
   used to compare and assess the military requirements of a country wrt
   other countries to meet the challenge of future battles. A measure of
   weighted directed-divergence based on m probability distributions has
   been proposed and a probability distribution `closest' to these m
   probability distributions is obtained. The closest probability
   distribution provides a reasonably adequate measure and thus enables one
   to apply this technique in real life situation, viz., assessment of
   balanced military requirements for a country: consensus ranking, pattern
   recognition, etc.}},
Publisher = {{DEFENCE SCIENTIFIC INFORMATION DOCUMENTATION CENTRE}},
Address = {{METCALFE HOUSE, DELHI 110054, INDIA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Tripathi, GP (Reprint Author), Inst Syst Studies \& Anal, Delhi 110054, India.
   Inst Syst Studies \& Anal, Delhi 110054, India.}},
ISSN = {{0011-748X}},
Research-Areas = {{Science \& Technology - Other Topics}},
Web-of-Science-Categories  = {{Multidisciplinary Sciences}},
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Number-of-Cited-References = {{16}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{0}},
Journal-ISO = {{Def. Sci. J.}},
Doc-Delivery-Number = {{300RK}},
Unique-ID = {{ISI:000086265800014}},
}

@article{ ISI:000080732100004,
Author = {Kim, SH and Ahn, BS},
Title = {{Interactive group decision making procedure under incomplete information}},
Journal = {{EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}},
Year = {{1999}},
Volume = {{116}},
Number = {{3}},
Pages = {{498-507}},
Month = {{AUG 1}},
Abstract = {{This paper deals with multiple criteria decision making problem with
   incomplete information when multiple decision makers (Multiple Criteria
   Group Decision Making: MCGDM) are involved. Usually decision makers
   (DMs) are willing or able to provide only incomplete information,
   because of time pressure, lack of knowledge or data, and their limited
   expertise related with problem domain. There have been just a few
   studies considering incomplete information in group settings. This
   incompletely specified information constructs region of linear
   constraints and therefore, pairwise dominance relationship between
   alternatives reduces to intractable nonlinear programmings. Hence, to
   handle this difficulty, we suggest a method, utilizing individual
   decision results to form group consensus. Final group consensus ranking
   toward more agreement of participants can be built through solving a
   series of linear programmings, using individual decision results under
   group members' possibly different weight constraints. (C) 1999 Elsevier
   Science B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Kim, SH (Reprint Author), Korea Adv Inst Sci \& Technol, Grad Sch Management, 207-43 Cheongryangri, Seoul 130012, South Korea.
   Korea Adv Inst Sci \& Technol, Grad Sch Management, Seoul 130012, South Korea.
   Suwon Univ, Dept Business Adm \& Accounting, Whasung 445743, Kyonggi, South Korea.}},
DOI = {{10.1016/S0377-2217(98)00040-X}},
ISSN = {{0377-2217}},
Keywords = {{decision theory; group preference aggregation; incomplete information;
   preference strength}},
Keywords-Plus = {{DOMINANCE}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
ResearcherID-Numbers = {{Kim, Soung Hie/C-1863-2011
   Ahn, Byeong Seok/D-3699-2013}},
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Number-of-Cited-References = {{25}},
Times-Cited = {{153}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{26}},
Journal-ISO = {{Eur. J. Oper. Res.}},
Doc-Delivery-Number = {{203WX}},
Unique-ID = {{ISI:000080732100004}},
}

@article{ ISI:000074494000017,
Author = {Charon, I and Hudry, O},
Title = {{Lamarckian genetic algorithms applied to the aggregation of preferences}},
Journal = {{ANNALS OF OPERATIONS RESEARCH}},
Year = {{1998}},
Volume = {{80}},
Pages = {{281-297}},
Abstract = {{The problem that we deal with consists in aggregating a set of
   individual preferences into a collective linear order summarizing the
   initial set as accurately as possible. As this problem is NP-hard, we
   apply heuristics to find good approximate solutions. More precisely, we
   design a Lamarckian genetic algorithm by hybridizing some
   meta-heuristics (based on the simulated annealing method or the noising
   method) with a genetic algorithm. For the problems that we studied, the
   experiments show that such a hybridization brings improvements to these
   already good methods.}},
Publisher = {{BALTZER SCI PUBL BV}},
Address = {{PO BOX 221, 1400 AE BUSSUM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Charon, I (Reprint Author), Ecole Natl Super Telecommun, 46 Rue Barrault, F-75634 Paris 13, France.
   Ecole Natl Super Telecommun, F-75634 Paris 13, France.}},
DOI = {{10.1023/A:1018976217274}},
ISSN = {{0254-5330}},
Keywords = {{aggregation of preferences; median order; Kemeny problem; Slater
   problem; genetic algorithm; simulated annealing; noising method;
   hybridization of heuristics}},
Keywords-Plus = {{COMBINATORIAL}},
Research-Areas = {{Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Operations Research \& Management Science}},
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Number-of-Cited-References = {{33}},
Times-Cited = {{13}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{0}},
Journal-ISO = {{Ann. Oper. Res.}},
Doc-Delivery-Number = {{ZX238}},
Unique-ID = {{ISI:000074494000017}},
}

@article{ ISI:A1997WB91900017,
Author = {Cook, WD and Kress, M and Seiford, LM},
Title = {{A general framework for distance-based consensus in ordinal ranking
   models}},
Journal = {{EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}},
Year = {{1997}},
Volume = {{96}},
Number = {{2}},
Pages = {{392-397}},
Month = {{JAN 24}},
Abstract = {{The problem of aggregating a set of ordinal rankings of n alternatives
   has given rise to a number of consensus models. Among the most common of
   these models are those due to Borda and Kendall, which amount to using
   average ranks, and the l(1) and l(2) distance models. A common criticism
   of these approaches is their use of ordinal rank position numbers
   directly as the values of being ranked at those levels. This paper
   presents a general framework for associating value or worth with ordinal
   ranks, and develops models for deriving a consensus based on this
   framework. It is shown that the l(p) distance models using this
   framework are equivalent to the conventional ordinal models for any p
   greater than or equal to 1. This observation can be seen as a form of
   validation of the practice of using ordinal data in a manner for which
   it was presumably not designed. In particular, it establishes the
   robustness of the simple Borda, Kendall and median ranking models.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Cook, WD (Reprint Author), YORK UNIV,FAC ADM STUDIES,N YORK,ON M3J 1P3,CANADA.
   CEMA,HAIFA,ISRAEL.
   UNIV MASSACHUSETTS,DEPT IND ENGN \& OPERAT RES,AMHERST,MA 01003.}},
DOI = {{10.1016/0377-2217(95)00322-3}},
ISSN = {{0377-2217}},
Keywords = {{ordinal; preference; ranking; consensus}},
Keywords-Plus = {{PRIORITY RANKING; PREFERENCE}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
Cited-References = {{DAVIS OA, 1972, ECONOMETRICA, V40, P147, DOI 10.2307/1909727.
   COOK WD, 1982, MANAGE SCI, V28, P621, DOI 10.1287/mnsc.28.6.621.
   ARMSTRONG RD, 1982, MANAGE SCI, V28, P638, DOI 10.1287/mnsc.28.6.638.
   Black Duncan, 1958, THEORY COMMITTEES EL.
   Borda J., 1781, HIST ACAD ROYALE SCI.
   BRIGHTWELL SA, 1978, CAHIERS CTR ETUDES R, V20, P59.
   COOK WD, 1990, MANAGE SCI, V36, P1302, DOI 10.1287/mnsc.36.11.1302.
   Cook W.D, 1978, MANAGE SCI, V24, P1721, DOI 10.1287/mnsc.24.16.1721.
   COOK WD, 1992, ORDINAL INFORMATION.
   KEESEY R, 1974, MODERN PARLIAMENTARY.
   Kendall M.G., 1962, RANK CORRELATION MET.
   RIKER WH, 1961, AM POLIT SCI REV, V5, P900.
   Roberts F. S., 1979, MEASUREMENT THEORY.}},
Number-of-Cited-References = {{13}},
Times-Cited = {{14}},
Usage-Count-(Last-180-days) = {{3}},
Usage-Count-Since-2013 = {{7}},
Journal-ISO = {{Eur. J. Oper. Res.}},
Doc-Delivery-Number = {{WB919}},
Unique-ID = {{ISI:A1997WB91900017}},
}

@article{ ISI:A1996VU49200003,
Author = {Tavana, M and Kennedy, DT and Joglekar, P},
Title = {{A group decision support framework for consensus ranking of technical
   manager candidates}},
Journal = {{OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE}},
Year = {{1996}},
Volume = {{24}},
Number = {{5}},
Pages = {{523-538}},
Month = {{OCT}},
Abstract = {{In many developed countries, today's socioeconomic environment has
   expanded the role of the technical manager. Organizations capable of
   recruiting technical managers with adequate management education and
   interpersonal skills, in addition to technical expertise, are more
   likely to be successful in managing their limited resources. A technical
   manager's success is also dependent on the manager's acceptance by
   his/her subordinates, peers, and superiors, and the decision to hire a
   technical manager should be made with their participation. Many of these
   individuals have little background or experience in hiring, and they
   need appropriate decision support. This paper presents a framework to
   help a group of decision makers define and articulate a hierarchy of
   hiring criteria and subcriteria and rate each of the candidates on that
   hierarchy. To improve consistency among group members, tbe proposed
   group decision support system (GDSS) combines the Analytic Hierarchy
   Process (AHP) with the Delphi principles of anonymous feedback and
   iteration. Given the decision makers' desire for a consensus choice, the
   framework deviates from the normal practice of AHP, and uses the
   Maximize Agreement Heuristic (MAH) to arrive at the final ranking of the
   candidates. An application to the ranking of nurse manager candidates at
   a hospital in the United States is presented. Copyright (C) 1996
   Elsevier Science Ltd}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD, ENGLAND OX5 1GB}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Tavana, M (Reprint Author), LA SALLE UNIV,DEPT MANAGEMENT,PHILADELPHIA,PA 19141, USA.}},
DOI = {{10.1016/0305-0483(96)00030-8}},
ISSN = {{0305-0483}},
Keywords = {{group decision support system; human resource selection; multicriteria
   decision making; Analytic Hierarchy Process; Maximize Agreement
   Heuristic; Delphi}},
Keywords-Plus = {{ANALYTIC HIERARCHY PROCESS; ORDINAL RANKING; ISSUES; PREFERENCE;
   INTENSITY; SELECTION; MODEL; TASK}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
Cited-References = {{Alavi M., 1991, Journal of Information Systems Management, V8.
   ALI I, 1986, MANAGE SCI, V32, P1642, DOI 10.1287/mnsc.32.12.1642.
   DALKEY N, 1963, MANAGE SCI, V9, P458, DOI 10.1287/mnsc.9.3.458.
   COOK DR, 1990, EUR J OPER RES, V48, P49.
   WEISS EN, 1987, DECISION SCI, V18, P43, DOI 10.1111/j.1540-5915.1987.tb01502.x.
   HARKER PT, 1987, MANAGE SCI, V33, P1383, DOI 10.1287/mnsc.33.11.1383.
   HALL NG, 1992, OPER RES, V40, P1040, DOI 10.1287/opre.40.6.1040.
   HAMALAINEN RP, 1990, EUR J OPER RES, V48, P66, DOI 10.1016/0377-2217(90)90062-G.
   PINSONNEAULT A, 1990, EUR J OPER RES, V46, P143, DOI 10.1016/0377-2217(90)90128-X.
   COOK WD, 1985, MANAGE SCI, V31, P26, DOI 10.1287/mnsc.31.1.26.
   BELTON V, 1986, EUR J OPER RES, V26, P7, DOI 10.1016/0377-2217(86)90155-4.
   DYER JS, 1990, MANAGE SCI, V36, P249, DOI 10.1287/mnsc.36.3.249.
   BECK MP, 1983, COMPUT OPER RES, V10, P1, DOI 10.1016/0305-0548(83)90021-7.
   JESSUP LM, 1990, MIS QUART, V14, P313, DOI 10.2307/248893.
   MALHOTRA MK, 1994, DECISION SCI, V25, P189, DOI 10.1111/j.1540-5915.1994.tb00800.x.
   MURALIDHAR K, 1990, INFORM MANAGE, V18, P87, DOI 10.1016/0378-7206(90)90055-M.
   HARKER PT, 1990, MANAGE SCI, V36, P269, DOI 10.1287/mnsc.36.3.269.
   LEWIS HS, 1993, DECISION SCI, V24, P1, DOI 10.1111/j.1540-5915.1993.tb00459.x.
   WINKLER RL, 1989, INT J FORECASTING, V5, P605, DOI 10.1016/0169-2070(89)90018-6.
   BARNUM BS, 1989, ESSENTIALS NURSING M.
   BARZILAI J, 1986, MANAGE SCI, V32, P1007, DOI 10.1287/mnsc.32.8.1007.
   BELTON V, 1983, OMEGA-INT J MANAGE S, V11, P228, DOI 10.1016/0305-0483(83)90047-6.
   BLIN JM, 1974, MANAGE SCI, V20, P1439, DOI 10.1287/mnsc.20.11.1439.
   BOWMAN VJ, 1973, MANAGE SCI, V19, P1029, DOI 10.1287/mnsc.19.9.1029.
   BROCKHOFF K, 1983, EUR J OPER RES, V13, P115, DOI 10.1016/0377-2217(83)90072-3.
   CASEBEER L, 1991, J NURSING STAFF  NOV, P271.
   CLIFFORD JC, 1982, ADV PROFESSIONAL NUR.
   Cook W.D, 1978, MANAGE SCI, V24, P1721, DOI 10.1287/mnsc.24.16.1721.
   Dalkey N, 1972, STUDIES QUALITY LIFE.
   DECKER PJ, 1992, NURSING ADM MICRO MA.
   DWYER DJ, 1992, J NURS ADMIN, V22, P17, DOI 10.1097/00005110-199202000-00020.
   FORMAN E, 1990, EXPERT CHOICE.
   Glendon K, 1992, Nurs Adm Q, V17, P69.
   HEGEDUS DM, 1986, J MANAGE, V12, P545, DOI 10.1177/014920638601200409.
   HOROWITZ I, 1972, Z NATIONALOKON, V32, P493, DOI 10.1007/BF01293425.
   HUDAK RP, 1993, HOSP HEALTH SERV ADM, V38, P181.
   MARK BA, 1994, J NURS ADMIN, V24, P48, DOI 10.1097/00005110-199401000-00013.
   MARQUIS B, 1994, MANAGEMENT DECISION.
   MARQUIS BL, 1992, MANAGEMENT DECISION.
   MARRINERTOMEY A, 1993, TRANSFORMATIONAL MEA.
   MARRINERTOMEY A, 1992, GUIDE NURSING MANAGE.
   Niederman F., 1991, MIS Q, V16, P474.
   PORTEROGRADY T, 1986, CREATIVE NURSING ADM.
   PREBLE JF, 1984, STRATEGIC MANAGE J, V5, P157, DOI 10.1002/smj.4250050206.
   Ross M E, 1992, J Health Care Mark, V12, P60.
   ROWLAND HS, 1992, NURSING ADM HDB.
   Saaty T., 1990, MULTICRITERIA DECISI.
   Saaty T. L, 1994, FUNDAMENTALS DECISIO.
   SAATY TL, 1986, MANAGE SCI, V32, P841, DOI 10.1287/mnsc.32.7.841.
   SMITH TC, 1993, J NURS ADMIN, V23, P38, DOI 10.1097/00005110-199309000-00010.
   SULLIVAN EJ, 1992, EFFECTIVE MANAGEMENT.
   Taylor F. W., 1911, PRINCIPLES SCI MANAG.
   WALSH A, 1992, J APPL BUSINESS RES, V9, P17.
   WATSON SR, 1982, OMEGA, V11, P13.
   WEINBERGER TE, 1992, COMPENSATION BENEFIT, V24, P61, DOI 10.1177/088636879202400115.
   WINKLER RL, 1992, OPERATIONAL RES, V40, P605.}},
Number-of-Cited-References = {{56}},
Times-Cited = {{19}},
Usage-Count-(Last-180-days) = {{4}},
Usage-Count-Since-2013 = {{12}},
Journal-ISO = {{Omega-Int. J. Manage. Sci.}},
Doc-Delivery-Number = {{VU492}},
Unique-ID = {{ISI:A1996VU49200003}},
}

@article{ ISI:A1995RL80700003,
Author = {ROBINSON, WC},
Title = {{PRICE OF MATERIALS AND COLLECTION DEVELOPMENT IN LARGER PUBLIC-LIBRARIES}},
Journal = {{LIBRARY ACQUISITIONS-PRACTICE AND THEORY}},
Year = {{1995}},
Volume = {{19}},
Number = {{3}},
Pages = {{299-312}},
Month = {{FAL}},
Abstract = {{Questionnaires were sent to public library systems in the 200 largest
   cities in the United States to learn more about the role of price in the
   selection of materials. A 34 percent response rate yielded 67 usable
   responses. When ranked on a scale from 1 to 7, with 7 being least
   important, list price had a median ranking of 5, while likely community
   demand was ranked 1. When faced with price increases, these collection
   developers tended to select fewer duplicates, fewer periodical and
   annual publications, and fewer nonbook items. About 26 percent of those
   responding had adopted an informal or formal price ceiling for
   selections. About 66 percent of these librarians were likely be more
   price conscious when selecting nonbook items. Price ceilings for
   categories and formats are discussed.}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD, ENGLAND OX5 1GB}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{ROBINSON, WC (Reprint Author), UNIV TENNESSEE,GRAD SCH LIB \& INFORMAT SCI,KNOXVILLE,TN 37996, USA.}},
DOI = {{10.1016/0364-6408(95)00024-4}},
ISSN = {{0364-6408}},
Keywords = {{PUBLIC LIBRARIES; PRICE; COLLECTION DEVELOPMENT}},
Research-Areas = {{Information Science \& Library Science}},
Web-of-Science-Categories  = {{Information Science \& Library Science}},
Cited-References = {{BOHNE H, 1976, SCHOLARLY PUBL, V7, P135.
   BOISSONNAS CM, 1989, LIBRARY ACQUISITIONS, V13, P78.
   BOWKER RR, 1993, BOWKER ANN LIBRARY B, P491.
   EAGLEN AB, 1979, SCH LIBRARY J, V25, P30.
   GRANNIS C, 1993, PUBLISHERS WEEKLY, V240, P532.
   LEVANT DJ, 1974, SCHOLARLY PUBL, V5, P319.
   LYNDEN FC, 1983, LIBRARY RESOURCES TE, V27, P14.
   ROBINSON WC, 1993, LIBR RESOUR TECH SER, V37, P351.
   SCILKEN MH, 1988, SCH LIBRARY J, V34, P6.
   SELSKY D, 1991, LIBR J, V116, P42.
   STLIFER E, 1993, LIBR J, V118, P16.
   STLIFER E, 1994, LIBR J, V119, P14.
   TRUCK L, 1994, E COMMUNICATION 0222.
   WALL CE, 1975, CATHOLIC LIBRARY WOR, V47, P170.
   1994, SCH LIBRARY J, V40, P14.
   1989, LIBRARIAN, V73, P10.
   1992, SCH LIBRARY J, V38, P16.
   1994, LIBR J, V241, P13.
   1994, LIBR J, V119, P15.
   1993, INFORMATION PLEASE A, P811.}},
Number-of-Cited-References = {{20}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{0}},
Journal-ISO = {{Libr. Acquis.-Pract. Theory}},
Doc-Delivery-Number = {{RL807}},
Unique-ID = {{ISI:A1995RL80700003}},
}

@article{ ISI:A1994PF35600006,
Author = {ANDRICH, D},
Title = {{UNFOLDING AND GROUP CONSENSUS RANKING FOR INDIVIDUAL-DIFFERENCES -
   VANBLOKLANDVOGELESANG,AW}},
Journal = {{JOURNAL OF MATHEMATICAL PSYCHOLOGY}},
Year = {{1994}},
Volume = {{38}},
Number = {{3}},
Pages = {{377-383}},
Month = {{SEP}},
Publisher = {{ACADEMIC PRESS INC JNL-COMP SUBSCRIPTIONS}},
Address = {{525 B ST, STE 1900, SAN DIEGO, CA 92101-4495}},
Type = {{Book Review}},
Language = {{English}},
DOI = {{10.1006/jmps.1994.1026}},
ISSN = {{0022-2496}},
Research-Areas = {{Mathematics; Mathematical Methods In Social Sciences; Psychology}},
Web-of-Science-Categories  = {{Mathematics, Interdisciplinary Applications; Social Sciences,
   Mathematical Methods; Psychology, Mathematical}},
Cited-References = {{VANBLOKLANDVOGE.AW, 1991, UNFOLDING GROUP CONC, P213.}},
Number-of-Cited-References = {{1}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{3}},
Journal-ISO = {{J. Math. Psychol.}},
Doc-Delivery-Number = {{PF356}},
Unique-ID = {{ISI:A1994PF35600006}},
}

@article{ ISI:A1994ND15200002,
Author = {TENG, JY and TZENG, GH},
Title = {{MULTICRITERIA EVALUATION FOR STRATEGIES OF IMPROVING AND CONTROLLING
   AIR-QUALITY IN THE SUPER CITY - A CASE-STUDY OF TAIPEI CITY}},
Journal = {{JOURNAL OF ENVIRONMENTAL MANAGEMENT}},
Year = {{1994}},
Volume = {{40}},
Number = {{3}},
Pages = {{213-229}},
Month = {{MAR}},
Abstract = {{The deterioration of air quality in big cities is closely related to
   transportation. Thus, the application of transportation means to
   improving and controlling the air quality of metropolitan areas is a
   correct and functioning method. Among several feasible improvement
   policies, transportation system management (TSM) is a kind of low-cost
   method which can be expected to show effects in a short-term period. It
   would necessitate a great deal of manpower, effort and time if each one
   of these methods were to be measured precisely and objectively. As a
   result, the utilization of an expert evaluation model to extract
   professional knowledge from various fields so as to locate views of
   consensus would result in a successful decision-making method under
   circumstances where information is incomplete.
   This paper puts forward three phases of a multicriteria evaluation model
   which will, at the onset, perform consensus elimination under key
   criteria so as to find out non-dominated strategies; next, every expert
   uses the ELECTRE III model to rank non-dominated strategies under
   multiple criteria; the consensus ranking method proposed by Cook and
   Seiford (1978) is then employed for uncovering the ranking of minimal
   recognition differences from all experts. This paper takes Taipei city
   as an illustration to elaborate the intended method.}},
Publisher = {{ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD}},
Address = {{24-28 OVAL RD, LONDON NW1 7DX, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{TENG, JY (Reprint Author), HUAFAN COLL HUMANITY \& TECHNOL, DEPT IND MANAGEMENT, 1 HUA FAN RD, SHIHTIN HSIANG, TAIPEI, TAIWAN.
   NATL CHIAO TUNG UNIV, ENERGY RES GRP, TAIPEI 100, TAIWAN.
   NATL CHIAO TUNG UNIV, INST TRAFF \& TRANSPORTAT, TAIPEI 100, TAIWAN.}},
DOI = {{10.1006/jema.1994.1016}},
ISSN = {{0301-4797}},
EISSN = {{1095-8630}},
Keywords = {{TSM STRATEGIES; AIR QUALITY; MCDM; ELECTRE III; CONSENSUS}},
Research-Areas = {{Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Environmental Sciences}},
ResearcherID-Numbers = {{Tzeng, Gwo-Hshiung/B-2775-2009}},
ORCID-Numbers = {{Tzeng, Gwo-Hshiung/0000-0003-1856-7497}},
Cited-References = {{MARTEL JM, 1986, EUR J OPER RES, V25, P258, DOI 10.1016/0377-2217(86)90090-1.
   ANANDALINGAM G, 1989, EUR J OPER RES, V43, P271, DOI 10.1016/0377-2217(89)90226-9.
   SAATY TL, 1977, J MATH PSYCHOL, V15, P234, DOI 10.1016/0022-2496(77)90033-5.
   BATCHELDER JH, 1983, 263 TRANSP RES BOARD.
   Cook W.D, 1978, MANAGE SCI, V24, P1721, DOI 10.1287/mnsc.24.16.1721.
   EBRAHIM A, 1986, TRANSPORT RES F-TRAF, V27, P30.
   HOROWITZ JL, 1976, DECISION MULTIPLE OB.
   LARWIN TF, 1976, TRANSPORT RES REC, V603, P49.
   LIMA PM, 1980, TRANSPORT RES REC, V770, P10.
   MAHAMASSANI H, 1983, ENVIRON PLANN B, V10, P193.
   ODUM EP, 1976, TRANSPORT RES REC, V561, P57.
   POLUS A, 1985, TRANSPORTATION RES R, V1081, P47.
   REINKE D, 1983, TRANSPORT RES REC, V912, P42.
   ROY B, 1986, EUR J OPER RES, V24, P318, DOI 10.1016/0377-2217(86)90054-8.
   STEVENS RD, 1987, VEHICULAR POLLUTION.
   Tzeng G.H., 1987, ENERGY SYSTEMS POLIC, V11, P1.
   TZENG GH, 1989, TRANSPORTATION, V4, P9.
   {*}US EPA, 1978, 600878004.
   WOHL M, 1990, TRANSPLANTATION INVE.
   WON J, 1990, URBAN STUD, V27, P119, DOI 10.1080/00420989020080071.}},
Number-of-Cited-References = {{20}},
Times-Cited = {{37}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{J. Environ. Manage.}},
Doc-Delivery-Number = {{ND152}},
Unique-ID = {{ISI:A1994ND15200002}},
}

@article{ ISI:A1993KZ34800002,
Author = {ENTWISTLE, KM},
Title = {{THE FRACTURE-STRESS OF FLOAT GLASS}},
Journal = {{JOURNAL OF MATERIALS SCIENCE}},
Year = {{1993}},
Volume = {{28}},
Number = {{8}},
Pages = {{2007-2012}},
Month = {{APR 15}},
Abstract = {{A fracture test {[}1 ] which uses concentrically loaded square plates
   supported near their corners has been used to measure the fracture
   stress of float glass. The plates were 1 02 mm square and 5.98 mm thick.
   The maximum displacement at fracture was less than 0.4 mm. Under these
   circumstances it has been shown that use of a linear finite element
   solution for the stress distribution and the plate deflections is
   justified. The glass plates had greater edge damage than had the alumina
   plates tested in an earlier investigation. In order to secure an
   adequate proportion of failures in the central plate region, it was
   necessary to move the supports inwards towards the centre of the plate.
   This reduced the ratio of the maximum edge stress to the maximum stress
   in the plate. Batches of plates were tested with loading circle
   diameters of 7.5 and 25 mm, to measure volume effects, with the side of
   the plate that had been in contact with the liquid tin in tension.
   Median ranking was used in the statistical analysis and edge failures
   were treated as suspensions, it being assumed that the minimum fracture
   stress of the central region of the edge-fractured plates was the plate
   centre stress at the fracture load. The Weibull modulus was determined
   by a linear regression in which extreme members of the population were
   given reduced weighting using the relationship of Faucher and Tyson
   {[}3]. The average fracture stresses were 147.2 and 107.3 N mm-2 for the
   7.5 and 25 mm loading circles, respectively, and the Weibull moduli were
   4.49 and 5.44. These data are shown to agree well with Weibull
   statistics. Tests using a 7.5 mm diameter loading circle on plates with
   the non-tin side in tension gave a significantly higher average fracture
   stress of 242.1 N mm-2, confirming the fact that the non-tin side has a
   higher strength.}},
Publisher = {{CHAPMAN HALL LTD}},
Address = {{2-6 BOUNDARY ROW, LONDON, ENGLAND SE1 8HN}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{ENTWISTLE, KM (Reprint Author), UMIST,MANCHESTER MAT SCI CTR,GROSVENOR ST,MANCHESTER M1 7HS,ENGLAND.}},
DOI = {{10.1007/BF00367556}},
ISSN = {{0022-2461}},
Research-Areas = {{Materials Science}},
Web-of-Science-Categories  = {{Materials Science, Multidisciplinary}},
Cited-References = {{FAUCHER B, 1988, J MATER SCI LETT, V7, P1199, DOI 10.1007/BF00722337.
   ENTWISTLE KM, 1991, J MATER SCI, V26, P1078.
   LIPSON C, 1973, STATISTICAL DESIGN A, P19.}},
Number-of-Cited-References = {{3}},
Times-Cited = {{13}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{J. Mater. Sci.}},
Doc-Delivery-Number = {{KZ348}},
Unique-ID = {{ISI:A1993KZ34800002}},
}

@article{ ISI:A1993KU50500001,
Author = {LEWIS, HS and BUTLER, TW},
Title = {{AN INTERACTIVE FRAMEWORK FOR MULTIPERSON, MULTIOBJECTIVE DECISIONS}},
Journal = {{DECISION SCIENCES}},
Year = {{1993}},
Volume = {{24}},
Number = {{1}},
Pages = {{1-22}},
Month = {{JAN-FEB}},
Abstract = {{Group decision making in the presence of multiple conflicting objectives
   is complex and difficult. This paper describes and evaluates an
   iterative technique to facilitate multiple objective decision making by
   multiple decision makers.  The proposed method augments an interactive
   multiobjective optimization procedure with a preference ranking tool and
   a consensus ranking heuristic. Two multiple objective linear programming
   (MOLP) solution approaches, the SIMOLP method of Reeves and Franz {[}39]
   and the interactive weighted Tchebycheff procedure of Steuer and Choo
   {[}49], are recommended optimization strategies to be used independently
   or in concert. Computational experience suggests that the proposed
   framework is an effective decision-making tool.  The procedure quickly
   located excellent compromise solutions in a series of test problems with
   hypothetical decision makers. In addition, human decision makers gave
   positive evaluations of the procedure and the production plans the
   procedure provided for a resource allocation case problem.}},
Publisher = {{DECISION SCIENCES INST, GEORGIA STATE UNIV}},
Address = {{COLLEGE OF BUSINESS ADMN, UNIVERSITY PLAZA, ATLANTA, GA 30303}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{LEWIS, HS (Reprint Author), PENN STATE UNIV,SMEAL COLL BUSINESS ADM,303 BEAM BUSINESS ADM BLDG,UNIV PK,PA 16802, USA.
   WAYNE STATE UNIV,SCH BUSINESS ADM,DEPT FINANCE \& BUSINESS ECON,DETROIT,MI 48202.}},
DOI = {{10.1111/j.1540-5915.1993.tb00459.x}},
ISSN = {{0011-7315}},
Keywords-Plus = {{PROGRAMMING METHOD; ORDINAL RANKING; OPTIMIZATION; CONSENSUS; SUPPORT;
   PREFERENCE; INTENSITY; SYSTEMS; MODELS; DELPHI}},
Research-Areas = {{Business \& Economics}},
Web-of-Science-Categories  = {{Management}},
Cited-References = {{ALI I, 1986, MANAGE SCI, V32, P1642, DOI 10.1287/mnsc.32.12.1642.
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Number-of-Cited-References = {{58}},
Times-Cited = {{26}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{Decis. Sci.}},
Doc-Delivery-Number = {{KU505}},
Unique-ID = {{ISI:A1993KU50500001}},
}

@article{ ISI:A1992JL28000024,
Author = {IZ, PH},
Title = {{2 MULTIPLE CRITERIA GROUP DECISION SUPPORT SYSTEMS BASED ON
   MATHEMATICAL-PROGRAMMING AND RANKING METHODS}},
Journal = {{EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}},
Year = {{1992}},
Volume = {{61}},
Number = {{1-2}},
Pages = {{245-253}},
Month = {{AUG 25}},
Note = {{1ST INTERNATIONAL SPECIALIZED CONF ON DECISION SUPPORT SYSTEMS (
   IFORS-SPC 1 ), BRUGES, BELGIUM, MAR 26-29, 1991}},
Organization = {{INT FEDERAT NATL OPERAT RES SOC; COUNCIL CITY BRUGES; VRIJE UNIV
   BRUSSELS; BELGIUM NATL FDN SCI RES; APPLE CTR BRUGES; APPLE CTR
   ROESELARE; COMPUVISION; COMSHARE BELGIUM; NATL BANK BELGIE}},
Abstract = {{This paper presents two prototype Group Decision Support Systems based
   on multiobjective linear programming. The emphasis of the paper is on
   the operationalization of multicriteria modelling techniques through
   group decision support technology. The major components of the prototype
   systems include procedures for generating efficient solutions,
   preference aggregation, and ranking alternatives. Empirical results from
   a laboratory application and their implications in terms of user
   preferences and system performance are also provided.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{IZ, PH (Reprint Author), UNIV BALTIMORE,DEPT INFORMAT \& QUANTITAT SCI,BALTIMORE,MD 21201, USA.}},
DOI = {{10.1016/0377-2217(92)90285-H}},
ISSN = {{0377-2217}},
Keywords = {{GROUP DECISION SUPPORT; PREFERENCE AGGREGATION; MULTIPLE OBJECTIVE
   PROGRAMMING; CONSENSUS RANKING}},
Keywords-Plus = {{PREFERENCE; OPTIMIZATION}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
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Number-of-Cited-References = {{34}},
Times-Cited = {{26}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Eur. J. Oper. Res.}},
Doc-Delivery-Number = {{JL280}},
Unique-ID = {{ISI:A1992JL28000024}},
}

@article{ ISI:A1992HQ00100020,
Author = {HENERY, RJ},
Title = {{UNFOLDING AND GROUP CONSENSUS RANKING FOR INDIVIDUAL PREFERENCES -
   VANBLOKLANDVOGELSANG,R}},
Journal = {{JOURNAL OF CLASSIFICATION}},
Year = {{1992}},
Volume = {{9}},
Number = {{1}},
Pages = {{176-178}},
Publisher = {{SPRINGER VERLAG}},
Address = {{175 FIFTH AVE, NEW YORK, NY 10010}},
Type = {{Book Review}},
Language = {{English}},
Affiliation = {{HENERY, RJ (Reprint Author), UNIV STRATHCLYDE,DEPT STAT,RICHMOND ST,GLASGOW G1 1XH,SCOTLAND.}},
DOI = {{10.1007/BF02618484}},
ISSN = {{0176-4268}},
Research-Areas = {{Mathematics; Psychology}},
Web-of-Science-Categories  = {{Mathematics, Interdisciplinary Applications; Psychology, Mathematical}},
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Number-of-Cited-References = {{8}},
Times-Cited = {{0}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{0}},
Journal-ISO = {{J. Classif.}},
Doc-Delivery-Number = {{HQ001}},
Unique-ID = {{ISI:A1992HQ00100020}},
}

@article{ ISI:A1986D560600008,
Author = {BARZILAI, J and COOK, WD and KRESS, M},
Title = {{A GENERALIZED NETWORK FORMULATION OF THE PAIRWISE COMPARISON CONSENSUS
   RANKING MODEL}},
Journal = {{MANAGEMENT SCIENCE}},
Year = {{1986}},
Volume = {{32}},
Number = {{8}},
Pages = {{1007-1014}},
Month = {{AUG}},
Publisher = {{INST OPERATIONS RESEARCH  MANAGEMENT SCIENCES}},
Address = {{901 ELKRIDGE LANDING RD, STE 400, LINTHICUM HTS, MD 21090-2909}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{BARZILAI, J (Reprint Author), DALHOUSIE UNIV,DEPT BUSINESS ADM,HALIFAX B3H 4H2,NS,CANADA.
   CTR MIL ANAL,HAIFA,ISRAEL.
   YORK UNIV,FAC ADM STUDIES,TORONTO M3J 2R6,ONTARIO,CANADA.}},
DOI = {{10.1287/mnsc.32.8.1007}},
ISSN = {{0025-1909}},
Research-Areas = {{Business \& Economics; Operations Research \& Management Science}},
Web-of-Science-Categories  = {{Management; Operations Research \& Management Science}},
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Number-of-Cited-References = {{19}},
Times-Cited = {{7}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{Manage. Sci.}},
Doc-Delivery-Number = {{D5606}},
Unique-ID = {{ISI:A1986D560600008}},
}
