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Mining Web Transaction Patterns in an Electronic Commerce Environment

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Knowledge Discovery and Data Mining. Current Issues and New Applications (PAKDD 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1805))

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Abstract

In this paper, we explore a new data mining capability which involves mining Web transaction patterns for an electronic commerce (EC) environment. We propose an innovative mining model that takes both the traveling patterns and purchasing patterns of customers into consideration. First, we develop algorithm WR to extract meaningful Web transaction records from Web transactions so as to filter out the effect of irrelevant traversal sequences. Second, we devise algorithm WTM for determining the large transaction patterns from the Web transaction records obtained.

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References

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, ROC

    Ching-Huang Yun & Ming-Syan Chen

Authors
  1. Ching-Huang Yun
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  2. Ming-Syan Chen
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Editor information

Editors and Affiliations

  1. Graduate School of Systems Management, Universiy of Tsukuba, 3-29-1 Otsuka, Bunkyo-ku, Tokyo, 112-0012, Japan

    Takao Terano

  2. Department of Computer Science and Engineering, Arizona State University, P.O. Box 875 406, Tempe, AZ, 85287-5406

    Huan Liu

  3. Department of Computer Science, National Tsing Hua University, Hsinchu, 300, Taiwan ROC

    Arbee L. P. Chen

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© 2000 Springer-Verlag Berlin Heidelberg

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Yun, CH., Chen, MS. (2000). Mining Web Transaction Patterns in an Electronic Commerce Environment. In: Terano, T., Liu, H., Chen, A.L.P. (eds) Knowledge Discovery and Data Mining. Current Issues and New Applications. PAKDD 2000. Lecture Notes in Computer Science(), vol 1805. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45571-X_28

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  • DOI: https://doi.org/10.1007/3-540-45571-X_28

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67382-8

  • Online ISBN: 978-3-540-45571-4

  • eBook Packages: Springer Book Archive

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