Clustering of Web Users Using Session-Based Similarity Measures

  • Authors:
  • Jitian Xiao;Yanchun Zhang

  • Affiliations:
  • -;-

  • Venue:
  • ICCNMC '01 Proceedings of the 2001 International Conference on Computer Networks and Mobile Computing (ICCNMC'01)
  • Year:
  • 2001

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Abstract

One important research topic in web usage mining is the clustering of web users based on their common properties. Informative knowledge obtained from web user clusters has been used for many applications, such as the prefetching of pages between web clients and proxies. This paper presents an approach for measuring similarity of interests among web users from their past access behaviors. The similarity measures are based on the user sessions extracted from the user's access logs. A multilevel scheme for clustering largenumber of web users is proposed, as an extension to the method proposed in our previous work [15]. Experiments have been conducted and the results have shown that our clustering method is capable of clustering web users with similar interests.