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

Autor:	Zhang, Dong, Zhao, Shu, Duan, Zhen, Chen, Jie, Zhang, Yangping, Tang, Jie
Rok vydání:	2019
Předmět:	Computer Science - Information Retrieval
Druh dokumentu:	Working Paper
Popis:	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 interesting that we also explore the paper-reviewer recommendation in the coarse-grained granularity. Comment: 21 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1912.08976 Zobrazit plný text záznamu View this record from Arxiv