Applications of Data Mining to Electronic Commerce

  • Ron Kohavi
  • Foster Provost

Abstract

Electronic commerce is emerging as the killer domain for data—mining technology. Is there support for such a bold statement? Data—mining technologies have been around for decades, without moving significantly beyond the domain of computer scientists, statisticians, and hard-core business analysts. Why are electronic commerce systems any different from other data—mining applications?

Keywords

Marketing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adomavicius, G. and Tuzhilin, A. 2001. Expert-driven validation of rule-based user models in personalization applications. Data Mining and Knowledge Discovery 5(l/2):33–58.MATHCrossRefGoogle Scholar
  2. Langley, P. and Simon, H.A. 1995. Applications of machine learning and rule induction. Communications of the ACM 38(11):54–64.CrossRefGoogle Scholar
  3. Lawrence, R.D., Almasi, G.S., Kotlyar, V., Viveros, M.S., and Duri, S.S. 2001. Personalization of supermarket product recommendations. Data Mining and Knowledge Discovery 5(1/2): 11–32.MATHCrossRefGoogle Scholar
  4. Lee, J., Podlaseck, M., Schonberg, E., and Hoch, R. 2001. Visualization and analysis of clickstream data of online stores for understanding web merchandising. Data Mining and Knowledge Discovery (this issue).Google Scholar
  5. Moore, G. and McKenna, R. 1995. Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers, Harperbusiness.Google Scholar
  6. Pazzani, M.J. 2000. Knowledge discovery from data? IEEE Intelligent Systems March/April 2000,10–13.Google Scholar
  7. Piatetsky-Shapiro, G., Brachman, R., Khabaza, T., Kloesgen, W., and Simoudis, E. 1996. An overview of issues in developing industrial data mining and knowledge discovery applications, in Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, AAAI Press, pp. 89–95.Google Scholar
  8. Provost, F. and Kohavi, R. 1998. Guest editors’ introduction: On applied research in machine learning. Machine Learning 30(2/3): 127–132.CrossRefGoogle Scholar
  9. Schafer, J.B., Konstan, J.A., and Riedl, J. 2001. E-commerce recommendation applications. Data Mining and Knowledge Discovery 5(1/2): 115–152.MATHCrossRefGoogle Scholar
  10. Spiliopoulou, M. and Pohle, C. 2001. Data mining for measuring and improving the success of web sites. Data Mining and Knowledge Discovery 5(1/2): 85–114.MATHCrossRefGoogle Scholar
  11. Underhill, P. 2000. Why We Buy: The Science of Shopping. Touchstone Books. Rockefeller Center, NY, New York.Google Scholar

Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Ron Kohavi
    • 1
  • Foster Provost
    • 2
  1. 1.Blue Martini SoftwareSan MateoUSA
  2. 2.New York UniversityNew YorkUSA

Personalised recommendations