An Efficient Data Mining Algorithm for Discovering Web Access Patterns

  • Show-Jane Yen
  • Yue-Shi Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2642)


In this paper, we propose a data mining technology to find non-simple frequent traversal patterns in a web environment where users can travel from one object to another through the corresponding hyperlinks. We keep track and remain the original user traversal paths in a web log, and apply the proposed data mining techniques to discover the complete traversal path which is traversed by a sufficient number of users, that is, non-simple frequent traversal patterns, from web logs. The non-simple frequent traversal patterns include forward and backward references, which are used to suggest potentially interesting traversal path to the users. The experimental results show that the discovered patterns can present the complete browsing paths traversed by most of the users and our algorithm outperforms other algorithms in discovered information and execution times.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Agrawal, R. and et al.: Mining Sequential Patterns. Proceedings of the International Conference on Data Engineering (ICDE), (1995) 3–14Google Scholar
  2. 2.
    Chen M.S., Park, J.S. and Yu, P.S.: Efficient Data Mining for Path Traversal Patterns. IEEE Transactions on Knowledge and Data Engineering (TKDE), (1998) 209–220Google Scholar
  3. 3.
    Pei, J., Han, J., Mortazavi-asi, B. and Zhu, H.: Mining Access Patterns Efficiently from Web Logs. Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), (2000) 396–407Google Scholar
  4. 4.
    Yen, S.J. and Lee, Y.S.: An Efficient Data Mining Technique for Discovering Interesting Sequential Patterns. Proceedings of the International Conference on Data Mining (ICDM), (2001) 663–664Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Show-Jane Yen
    • 1
  • Yue-Shi Lee
    • 2
  1. 1.Department of Computer Science & Information ManagementFu Jen Catholic UniversityTaipeiTaiwan, R.O.C.
  2. 2.Department of Information ManagementMing Chuan UniversityTaoyuan CountyTaiwan, R.O.C.

Personalised recommendations