Data Mining and Knowledge Discovery

, Volume 6, Issue 1, pp 5–8 | Cite as

Web Mining

  • Ron Kohavi
  • Brij Masand
  • Myra Spiliopoulou
  • Jaideep Srivastava


Artificial Intelligence Data Structure Information Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Kohavi, R. 2001. Mining e-commerce data: The Good, the Bad, and the Ugly (invited industrial track talk). In Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, F. Provost and R. Srikant (Eds.). Aug. 2001. http://robotics.Stanford.EDU/users/ronnyk/goodBadUglyKDDItrack.pdf Google Scholar
  2. Kosala, R. and Blockeel, H. 2000.Web mining research: A survey, ACM SIGKDD Explorations, 2(1). Google Scholar
  3. Masand, B. and Spiliopoulou, M. (Eds.). 2000. Advances in Web Usage Mining and User Profiling: Proceedings of the WEBKDD'99 Workshop, Springer Verlag, July 2000. LNAI, Vol. 1836. (BibTeX Entry)Google Scholar
  4. b_1/103-2009916-9046229Google Scholar
  5. Srivastava, J., Cooley, R., Deshpande, M., and Tan, P. 2000.Web usage mining: Discovery and applications of web usage patterns from web data, ACM SIGKDD Explorations, 1(2). Google Scholar

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Ron Kohavi
    • 1
  • Brij Masand
    • 2
  • Myra Spiliopoulou
    • 3
  • Jaideep Srivastava
    • 4
  1. 1.Blue Martini SoftwareSan MateoUSA
  2. 2.VerilyticsBurlingtonUSA
  3. 3.Department of E-BusinessLeipzig Graduate School of Management (HHL)LeipzigGermany
  4. 4.Computer Science & EngineeringUniversity of MinnesotaMinneapolisUSA

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