Peer review expert group recommendation: A multi-subject coverage-based approach - Fu, Yongfan; Luo, Jian; Nan, Guofang; Li, Dahui (Expert systems with applications, 2025)
The role of peer reviewers in the peer review process is crucial for determining the quality and suitability of submitted manuscripts for publication. Previous studies on the Reviewer Assignment Problem (RAP) have primarily focused on assigning reviewers independently, considering the match between each reviewer and the manuscript while neglecting subject diversity. In this paper, we propose a group-based recommendation approach for selecting an appropriate peer review expert group. To achieve this, we construct a weighted heterogeneous network based on the reviewer’s publications to capture the reviewer’s subject interest and expertise. We then introduce a group-based reviewer recommendation model that formulates RAP as a Binary Integer Programming (BIP) problem. In the general module in the model, we develop a novel heuristic algorithm to implement BIP, identifying the optimal combination of reviewers as the recommended peer review expert group. Furthermore, to address situations where recommended reviewers decline review invitations, we propose an improved heuristic algorithm that provides supplementary reviewers within the group-based recommendation model. Finally, through a series of experiments, we demonstrate that our proposed approach outperformed previous well-known methods for RAP. In summary, our approach facilitates an efficient assembly of a reviewer group by editors to address issues in RAP.