TY - JOUR
T1 - A decision support tool using Order Weighted Averaging for conference review assignment
AU - Nguyen, Jennifer
AU - Sánchez-Hernández, Germán
AU - Agell, N.
AU - Rovira Llobera, X.
AU - Angulo, Cecilio
N1 - Funding Information:
This research was partly supported by the INVITE research project ( TIN2016-80049-C2-1-R and TIN2016-80049-C2-2-R ), funded by the Spanish Ministry of Economy and Competitiveness . The research has been partially supported with funds from Obra Social “la Caixa”. The authors would like to acknowledge the support of Professor Ramon López de Mántaras for the validation of the results obtained. His collaboration is very much appreciated.
Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2018/4/1
Y1 - 2018/4/1
N2 - Assigning papers to reviewers is a large, long and difficult task for conference chairs and scientific committees. The paper reviewer assignment problem is a multi-agent problem which requires understanding reviewer expertise and paper topics for the matching process. This paper proposes to elaborate on some features used to compute reviewer expertise and aggregate multiple factors to find the fittest combination of reviewers for each paper. Expertise information is gathered implicitly from publicly available information and a reviewer profile is generated automatically. An Ordered Weighted Averaging (OWA) aggregation function is used to summarize information coming from different sources and rank candidate reviewers for each paper. General constraints for the Reviewer Assignment Problem (RAP) have been incorporated into a real case example: (i) conflicts of interest between a reviewer and authors should be avoided, (ii) each paper must have a minimum number of reviewers, and (iii) each reviewer load cannot exceed a certain number of papers.
AB - Assigning papers to reviewers is a large, long and difficult task for conference chairs and scientific committees. The paper reviewer assignment problem is a multi-agent problem which requires understanding reviewer expertise and paper topics for the matching process. This paper proposes to elaborate on some features used to compute reviewer expertise and aggregate multiple factors to find the fittest combination of reviewers for each paper. Expertise information is gathered implicitly from publicly available information and a reviewer profile is generated automatically. An Ordered Weighted Averaging (OWA) aggregation function is used to summarize information coming from different sources and rank candidate reviewers for each paper. General constraints for the Reviewer Assignment Problem (RAP) have been incorporated into a real case example: (i) conflicts of interest between a reviewer and authors should be avoided, (ii) each paper must have a minimum number of reviewers, and (iii) each reviewer load cannot exceed a certain number of papers.
KW - Conference reviewer assignment
KW - Decision support systems
KW - OWA
UR - http://www.scopus.com/inward/record.url?scp=85029607113&partnerID=8YFLogxK
U2 - 10.1016/j.patrec.2017.09.020
DO - 10.1016/j.patrec.2017.09.020
M3 - Article
AN - SCOPUS:85029607113
SN - 0167-8655
VL - 105
SP - 114
EP - 120
JO - Pattern Recognition Letters
JF - Pattern Recognition Letters
ER -