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A multi-label classification method using a hierarchical and transparent representation for paper-reviewer recommendation
[article]
2019
arXiv
pre-print
Preserved Fulltext
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
arXiv:1912.08976v1
fatcat:c2sb7yupjrgz3alzfudcflup2y