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An Efficient Data Mining Algorithm for Discovering Web Access Patterns

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Web Technologies and Applications (APWeb 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2642))

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Abstract

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.

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References

  1. Agrawal, R. and et al.: Mining Sequential Patterns. Proceedings of the International Conference on Data Engineering (ICDE), (1995) 3–14

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  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) 663–664

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© 2003 Springer-Verlag Berlin Heidelberg

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Yen, SJ., Lee, YS. (2003). An Efficient Data Mining Algorithm for Discovering Web Access Patterns. In: Zhou, X., Orlowska, M.E., Zhang, Y. (eds) Web Technologies and Applications. APWeb 2003. Lecture Notes in Computer Science, vol 2642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36901-5_20

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  • DOI: https://doi.org/10.1007/3-540-36901-5_20

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-02354-8

  • Online ISBN: 978-3-540-36901-1

  • eBook Packages: Springer Book Archive

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