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An Evolutionary Approach for Clustering User Access Patterns from Web Logs

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AI 2006: Advances in Artificial Intelligence (AI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4304))

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Abstract

In this paper rough c-means is applied to cluster user access patterns, in which PSO(Particle Swarm Optimization) algorithm is employed to tune the threshold and relative importance of upper and lower approximations. The Davies-Bouldin clustering validity index is used as the fitness function that is minimized while arriving at an optimal clustering. The effectiveness of the algorithm is demonstrated by an experiment.

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Author information

Authors and Affiliations

  1. School of Mathematics and Computer Science, Shanxi Normal University, Shanxi, 041004, China

    Rui Wu

Authors
  1. Rui Wu
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Editor information

Editors and Affiliations

  1. DisPRR, National ICT Australia Ltd, QLD, Australia

    Abdul Sattar

  2. School of Computing, University of Tasmania, Sandy Bay, 7005, Tasmania, Australia

    Byeong-ho Kang

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© 2006 Springer-Verlag Berlin Heidelberg

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Wu, R. (2006). An Evolutionary Approach for Clustering User Access Patterns from Web Logs. In: Sattar, A., Kang, Bh. (eds) AI 2006: Advances in Artificial Intelligence. AI 2006. Lecture Notes in Computer Science(), vol 4304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941439_145

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  • DOI: https://doi.org/10.1007/11941439_145

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-49787-5

  • Online ISBN: 978-3-540-49788-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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