Abstract
To provide assistance with tasks such as retrieving USENET news articles or identifying interesting Web pages, an intelligent agent requires information about a user’s interests and needs. Machine learning techniques are now being used to acquire this information. A general architecture is presented, and two approaches to learning through observation are described. An instantiation of the architecture is then evaluated.
Original language | English |
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Title of host publication | Proceedings of AAAI 1996 Stanford Spring Symposium on Machine Learning in Information Access |
Editors | Marti A Hearst, Haym Hirsh |
Place of Publication | Menlo Park, CA |
Publisher | AAAI Press |
Pages | 31-40 |
Volume | SS-96-05 |
Publication status | Published - 1996 |
Keywords
- user agents
- user profiling
- machine learning
- USENET
- Web