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Title: Paper-to-reviewer assignment, based on expertise degree of reviewers and relevance degree between reviewers and papers

Authors: Xinlian Li; Toyohide Watanabe

Addresses: Graduate School of Information Science, Nagoya University, Furu-cho, Chikusa-ku, Nagoya 464-8603, Japan ' Nagoya Industrial Science Research Institute, c/o Corp. Mizuno, 2-1-16 Seimeiyama, Chikusa-ku, Nagoya 464-0087, Japan

Abstract: Automating the process of paper-to-reviewer assignment is a difficult task to be adequately resolved. Many papers concerning the related topics have been published, but there is still scare of systematic research applications. In most real world conference management, the assignment task is carried out manually by the programme committee, lacking of intelligent assigning rules and efficient matching method. The manual assignment is not only of low efficiency but also does not guarantee to result in the best solution. Given such situation, our paper sets out to analyse the problem of reviewer selection and propose a method for automatically matching papers with reviewers. Our objective is to reduce the loads of both programme committee and reviewers and make the conference-paper assignment task effectual. In this paper, we address this issue of paper-to-reviewer assignment and propose a method to model reviewers, based on the matching degree between reviewers and papers by combining preference-based approach and topic-based approach. We explain the assignment algorithm and show the evaluation results in comparison with Hungarian algorithm.

Keywords: paper-to-reviewer assignment; Hungarian algorithm; matching degree; expertise degree; relevance degree; paper review process; reviewer selection; modelling; preference approach; topic approach.

DOI: 10.1504/IJKWI.2014.065062

International Journal of Knowledge and Web Intelligence, 2014 Vol.5 No.1, pp.1 - 20

Published online: 25 Oct 2014 *

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