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

Dong Zhang, Shu Zhao, Zhen Duan, Jie Chen, Yangping Zhang, Jie Tang
2019 arXiv   pre-print
Paper-reviewer recommendation task is of significant academic importance for conference chairs and journal editors. How to effectively and accurately recommend reviewers for the submitted papers is a meaningful and still tough task. In this paper, we propose a Multi-Label Classification method using a hierarchical and transparent Representation named Hiepar-MLC. Further, we propose a simple multi-label-based reviewer assignment MLBRA strategy to select the appropriate reviewers. It is
more » ... g that we also explore the paper-reviewer recommendation in the coarse-grained granularity.
arXiv:1912.08976v1 fatcat:c2sb7yupjrgz3alzfudcflup2y