TOAST: A Topic-Oriented Tag-Based Recommender System

  • Guandong Xu
  • Yanhui Gu
  • Yanchun Zhang
  • Zhenglu Yang
  • Masaru Kitsuregawa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6997)


Social Annotation Systems have emerged as a popular application with the advance of Web 2.0 technologies. Tags generated by users using arbitrary words to express their own opinions and perceptions on various resources provide a new intermediate dimension between users and resources, which deemed to convey the user preference information. Using clustering for topic extraction and incorporating it with the capture of user preference and resource affiliation is becoming an effective practice in tag-based recommender systems. In this paper, we aim to address these challenges via a topic graph approach. We first propose a Topic Oriented Graph (TOG), which models the user preference and resource affiliation on various topics. Based on the graph, we devise a Topic-Oriented Tag-based Recommendation System (TOAST) by using the preference propagation on the graph. We conduct experiments on two real datasets to demonstrate that our approach outperforms other state-of-the-art algorithms.


Bipartite Graph Recommender System Preference Propagation Topic Information Personalized Recommendation 
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

  • Guandong Xu
    • 1
  • Yanhui Gu
    • 2
  • Yanchun Zhang
    • 1
  • Zhenglu Yang
    • 3
  • Masaru Kitsuregawa
    • 3
  1. 1.School of Engineering and ScienceVictoria UniversityAustralia
  2. 2.Dept. of Information and Communication EngineeringUniversity of TokyoJapan
  3. 3.Institute of Industrial ScienceUniversity of TokyoJapan

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