Clustering Web Transactions Using Fuzzy Rough− k Means

  • Rui Wu
  • Peilin Shi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 30)

Abstract

Whether a web page is visited or not and its time duration reveal web user’s interest. In this paper, web access pattern disclosing user unique interest is transformed as a fuzzy vector with the same length, in which each element is a fuzzy linguistic variable or 0 denoting the visited web page and its fuzzy time duration. Then we proposed a modified rough k-means clustering algorithm based on properties of rough variable to group the gained fuzzy web access patterns. Finally, an example is provided to illustrate the clustering process. Using this approach, web transactions with the same or similar behavior can be grouped into one class.

Keywords

clustering web mining fuzzy variable rough variable web access patterns 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Rui Wu
    • 1
  • Peilin Shi
    • 2
  1. 1.School of Mathematics and Computer ScienceShanxi Normal UniversityLinfenChina
  2. 2.Department of MathematicsTaiyuan University of TechnologyTaiyuanChina

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