On Good and Fair Paper-Reviewer Assignment

Cheng Long, Raymond Chi-Wing Wong, Yu Peng, Liangliang Ye

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Citations (Scopus)

Abstract

Peer review has become the most common practice for judging papers submitted to a conference for decades. An extremely important task involved in peer review is to assign submitted papers to reviewers with appropriate expertise which is referred to as paper-reviewer assignment. In this paper, we study the paper-reviewer assignment problem from both the goodness aspect and the fairness aspect. For the goodness aspect, we propose to maximize the topic coverage of the paper-reviewer assignment. This objective is new and the problem based on this objective is shown to be NP-hard. To solve this problem efficiently, we design an approximate algorithm which gives a 1/3-approximation. For the fairness aspect, we perform a detailed study on conflict-of-interest (COI) types and discuss several issues related to using COI, which, we hope, can raise some open discussions among researchers on the COI study. Finally, we conducted experiments on real datasets which verified the effectiveness of our algorithm and also revealed some interesting results of COI.
Original languageEnglish
Title of host publication2013 IEEE 13th International Conference on Data Mining
Place of PublicationDallas, USA
PublisherIEEE Computer Society
Pages1145-1150
Number of pages6
Publication statusPublished - 2013
Externally publishedYes

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