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A Pattern-Based Academic Reviewer Recommendation Combining Author-Paper and Diversity Metrics
2019
IEEE Access
With the rapid increase of publishable research articles and manuscripts, the pressure to find reviewers often overwhelms the journal editors. This paper incorporates the major entity level metrics found in the heterogeneous publication networks into a pattern mining process in order to recommend academic reviewers and potential research collaborators. In essence, the paper integrates authors' h-index and papers' citation count and proposes a quantification to account for the author diversity
doi:10.1109/access.2019.2894680
fatcat:3i7jmzhyobc3fbrwefkemojivu