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

An integer linear programming model of reviewer assignment with research interest considerations Ann Oper Res https://doi.org/10.1007/s10479-018-2919-7 S.I.: REALCASEOR An integer linear programming model of reviewer assignment with research interest considerations 1 2 3 1 Jian Jin · Baozhuang Niu · Ping Ji · Qian Geng © Springer Science+Business Media, LLC, part of Springer Nature 2018 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 num- ber 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 program- ming problem is formulated with practical considerations to recommend reviewers for a group of submissions. Specifically, the topical relevance and the topical authority are uti- lized 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, com- pared with benchmark approaches, the proposed approach is capable to capture the research interest of http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Operations Research Springer Journals

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

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Publisher
Springer US
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Business and Management; Operations Research/Decision Theory; Combinatorics; Theory of Computation
ISSN
0254-5330
eISSN
1572-9338
D.O.I.
10.1007/s10479-018-2919-7
Publisher site
See Article on Publisher Site

Abstract

Ann Oper Res https://doi.org/10.1007/s10479-018-2919-7 S.I.: REALCASEOR An integer linear programming model of reviewer assignment with research interest considerations 1 2 3 1 Jian Jin · Baozhuang Niu · Ping Ji · Qian Geng © Springer Science+Business Media, LLC, part of Springer Nature 2018 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 num- ber 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 program- ming problem is formulated with practical considerations to recommend reviewers for a group of submissions. Specifically, the topical relevance and the topical authority are uti- lized 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, com- pared with benchmark approaches, the proposed approach is capable to capture the research interest of

Journal

Annals of Operations ResearchSpringer Journals

Published: Jun 4, 2018

References

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