Open AccessLearning Probabilistic User Profiles
Author(s) -
Ackerman Mark,
Billsus Daniel,
Gaffney Scott,
Hettich Seth,
Khoo Gordon,
Kim Dong Joon,
Klefstad Ray,
Lowe Charles,
Ludeman Alexius,
Muramatsu Jack,
Omori Kazuo,
Pazzani Michael J.,
Semler Douglas,
Starr Brian,
Yap Paul
Publication year - 1997
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v18i2.1293
Subject(s) - probabilistic logic , world wide web , computer science , rank (graph theory) , information retrieval , artificial intelligence , mathematics , combinatorics
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.