FolkDiffusion: A Graph-Based Tag Suggestion Method for Folksonomies

  • Zhiyuan Liu
  • Chuan Shi
  • Maosong Sun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6458)

Abstract

Collaborative social tagging is a popular and convenient way to organize web resources. All tags compose into a semantic structure named as folksonomies. Automatic tag suggestions can ease tagging activities of users. Various methods have been proposed for tag suggestions, which are roughly categorized into two approaches: content-based and graph-based. In this paper we present a heat diffusion method, i.e., FolkDiffusion, to rank tags for tag suggestions. Compared to existing graph-based methods, FolkDiffusion can suggest user- and resource-specific tags and prevent from topic drift. Experiments on real online social tagging datasets show the efficiency and effectiveness of FolkDiffusion compared to existing graph-based methods.

Keywords

Folksonomies tag suggestions FolkDiffusion heat diffusion 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Zhiyuan Liu
    • 1
    • 3
    • 4
  • Chuan Shi
    • 2
    • 3
    • 4
  • Maosong Sun
    • 1
    • 3
    • 4
  1. 1.Department of Computer Science and TechnologyTsinghua UniversityChina
  2. 2.Department of Electronic EngineeringTsinghua UniversityChina
  3. 3.State Key Lab on Intelligent Technology and SystemsTsinghua UniversityChina
  4. 4.National Lab for Information Science and TechnologyTsinghua UniversityChina

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