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
Annals of Operations Research – Springer Journals
Published: Jun 4, 2018
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