  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.
