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Paper-reviewer recommendation task is of significant academic importance forconference chairs and journal editors. How to effectively and accuratelyrecommend reviewers for the submitted papers is a meaningful and still toughtask. In this paper, we propose a Multi-Label Classification method using ahierarchical and transparent Representation named Hiepar-MLC. Further, wepropose a simple multi-label-based reviewer assignment MLBRA strategy to selectthe appropriate reviewers. It is interesting that we also explore thepaper-reviewer recommendation in the coarse-grained granularity.

A multi-label classification method using a hierarchical and transparent representation for paper-reviewer recommendation