Co-Ranking Multiple Entities in a Heterogeneous Network: Integrating Temporal Factor and Users' Bookmarks

In this paper, we present a novel approach that models the mutual reinforcing relationship among papers, authors and publication venues with due cognizance of publication time. We further integrate bookmark information which models the relationship between users' expertise and papers' quality into the composite citation network using random walk with restart framework. The experimental results with ACM dataset show that 1) the proposed method outperforms the traditional methods; 2) by incorporating the temporal factor, the ranking result of latest publications can be greatly improved; 3) the integration of user generated content further enhances the ranking result.