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

  • Ming Zhang
  • Sheng Feng
  • Jian Tang
  • Bolanle Ojokoh
  • Guojun Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7008)


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.


Random Walk Heterogeneous Network Temporal Factor Citation Network Ranking Result 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ming Zhang
    • 1
  • Sheng Feng
    • 1
  • Jian Tang
    • 1
  • Bolanle Ojokoh
    • 1
    • 2
  • Guojun Liu
    • 1
  1. 1.Institute of Networking and Information Systems, School of Electronics Engineering and Computer SciencePeking UniversityBeijingChina
  2. 2.Department of Computer ScienceFederal University of TechnologyAkureNigeria

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