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An integer linear programming model of reviewer assignment with research interest considerations

  • S.I.: RealCaseOR
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Abstract

In the regular work process of peer review, editors have to read and understand the entire set of submissions to choose appropriate reviewers. However, due to a large number of submissions, to select reviewers manually becomes error-prone and time-consuming. In this research, a framework that considers different indispensable aspects such as topical relevance, topical authority and research interest is presented and, an integer linear programming problem is formulated with practical considerations to recommend reviewers for a group of submissions. Specifically, the topical relevance and the topical authority are utilized to recommend relevant and accredited candidates in submission-related topics, while the research interest is to exam the willingness of candidates to review a submission. To evaluate the effectiveness of the proposed approach, categories of comparative experiments were conducted on two large scholarly datasets. Experimental results demonstrate that, compared with benchmark approaches, the proposed approach is capable to capture the research interest of reviewer candidates without a significant loss in different evaluation metrics. Our work can be helpful for editors to invite matching experts in peer review and highlight the necessity to uncover valuable information from big scholarly data for expert selection.

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Acknowledgements

This research was supported by NSFC (No. 71571194, 71701019), the youth fund project of ministry of education of the humanities and social sciences research (No. 16YJC870006), the fundamental research funds for the central universities (No. SKZZB2014037), Chang Jiang Scholars Program (Niu Baozhuang 2017), GDUPS (Niu Baozhuang 2017), Guangdong Soft Science Project (No. 2016A070705019), and ITF Project (No. K-ZM25).

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Authors and Affiliations

  1. Department of Information Management, Beijing Normal University, Beijing, 100875, China

    Jian Jin & Qian Geng

  2. School of Business Administration, South China University of Technology, Guangzhou, 510006, China

    Baozhuang Niu

  3. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

    Ping Ji

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  1. Jian Jin
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  2. Baozhuang Niu
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Correspondence to Baozhuang Niu.

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Jin, J., Niu, B., Ji, P. et al. An integer linear programming model of reviewer assignment with research interest considerations. Ann Oper Res 291, 409–433 (2020). https://doi.org/10.1007/s10479-018-2919-7

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