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Tag Based Collaborative Filtering for Recommender Systems

  • Huizhi Liang
  • Yue Xu
  • Yuefeng Li
  • Richi Nayak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5589)

Abstract

Collaborative tagging can help users organize, share and retrieve information in an easy and quick way. For the collaborative tagging information implies user’s important personal preference information, it can be used to recommend personalized items to users. This paper proposes a novel tag-based collaborative filtering approach for recommending personalized items to users of online communities that are equipped with tagging facilities. Based on the distinctive three dimensional relationships among users, tags and items, a new similarity measure method is proposed to generate the neighborhood of users with similar tagging behavior instead of similar implicit ratings. The promising experiment result shows that by using the tagging information the proposed approach outperforms the standard user and item based collaborative filtering approaches.

Keywords

Collaborative filtering collaborative tagging recommender systems user profiling 

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Huizhi Liang
    • 1
  • Yue Xu
    • 1
  • Yuefeng Li
    • 1
  • Richi Nayak
    • 1
  1. 1.School of Information TechnologyQueensland University of TechnologyBrisbaneAustralia

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