数字图书馆论坛Issue(4)：47-55,9.DOI:10.3772/j.issn.1673-2286.2017.04.007
基于主题契合度的专家推荐模型研究
A Topic Relevance Aware Model for Reviewer Recommendation
摘要
Abstract
Reviewer assignment is an important step in the phase of paper evaluation for conference organizers and journal editors. In this study, the importance of a topic is initially estimated by its occurrence frequency within a specific research area, which helps to express submissions and reviewers' expertise. Next, in consideration of topic importance in submissions, an integer optimization model is formulated to recommend a reviewer group. Also, different practical constraints are reckoned in the optimization model, which includes the affinity between reviewers and submissions, reviewers' expertise, the burden assignment of each reviewer, etc. To evaluate the effectiveness, the proposed approach is benchmarked with two baseline algorithms in terms of coverage, average number of reviewers, relevance between reviewers and topics, etc. Comparative experiment results show that the proposed approach is capable to recommend reviewers effectively.关键词
评审专家推荐/主题契合度/整数优化Key words
Reviewer Assignment/Topic Relevance/Integer Optimization分类
信息技术与安全科学引用本文复制引用
靳健,杨海慈,李凝,耿骞..基于主题契合度的专家推荐模型研究[J].数字图书馆论坛,2017,(4):47-55,9.基金项目
本研究得到教育部人文社会科学研究青年基金项目"面向论文评审专家推荐的兴趣变化挖掘与回避机制生成的研究"(编号:16YJC870006)和ISTIC-EBSCO文献大数据发现服务联合实验室基金项目"融合异构科研数据的评审专家推荐研究"资助. （编号:16YJC870006）
