Learning Probabilistic User Profiles: Applications for Finding Interesting Web Sites, Notifying Users of Relevant Changes to Web Pages, and Locating Grant Opportunities

  • Mark Ackerman
  • Daniel Billsus
  • Scott Gaffney
  • Gordon Khoo
  • Seth Hettich
  • Dong Joon Kim
  • Ray Klefstad
  • Charles Lowe
  • Alexius Ludeman
  • Jack Muramatsu
  • Kazuo Omori
  • Michael J. Pazzani
  • Douglas Semler
  • Brian Starr
  • Paul Yap

Abstract

This article describes three agents that help a user locate useful or interesting information on the World Wide Web. The agents learn a probabilistic profile to find, classify, or rank other sources of information that are likely to interest the user.
Published
1997-06-15
How to Cite
Ackerman, M., Billsus, D., Gaffney, S., Khoo, G., Hettich, S., Kim, D. J., Klefstad, R., Lowe, C., Ludeman, A., Muramatsu, J., Omori, K., Pazzani, M. J., Semler, D., Starr, B., & Yap, P. (1997). Learning Probabilistic User Profiles: Applications for Finding Interesting Web Sites, Notifying Users of Relevant Changes to Web Pages, and Locating Grant Opportunities. AI Magazine, 18(2), 47. https://doi.org/10.1609/aimag.v18i2.1293
Section
Articles