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Dynamic Semantic Clustering Approach for Web User Interest

  • Jiu Jun Chen
  • Ji Gao
  • Bei Shui Liao
  • Jun Hu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3252)

Abstract

To extract a dynamic interest model, we proposed an approach to mine multilayer interests from navigational behavior and favorite pages of web user. Our works based on the ideas that changes of the user interests can be tracked from his or her navigational behavior, and the changeable interests might derivate from the same kind of interests at a higher abstraction level. Markov user model (MUM) is used to learn the navigational characters of web user. Based on both MUM and user’s favorite pages, dynamic semantic mining approach is designed to construct multilayer user interest, which represents the user’s specific as well as general interests. The higher-level interests are more general, and the lower-level ones are more specific. The model implements in our example website to mine the dynamic continuum of long-term to short-term interests of web user. It proves that the results are good.

Keywords

User Profile User Interest Probabilistic Latent Semantic Analysis Semantic Cluster Leaf Cluster 
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 2004

Authors and Affiliations

  • Jiu Jun Chen
    • 1
  • Ji Gao
    • 1
  • Bei Shui Liao
    • 1
  • Jun Hu
    • 1
  1. 1.College of Computer ScienceZhejiang UniversityHangzhou, ZhejiangChina

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