Abstract
The rapid growth of the Internet and the World Wide Web (Web) provides access to vast amounts of valuable information. However, the problem of information overload is an obstacle to the practical use of potentially useful information on the Web. Agent based information filtering alleviates the above problem by proactively scanning through the incoming stream of information on behalf of the users. However, users’ information needs will change over time. To make intelligent information filtering effective, the agents must be adaptive. The AGM belief revision framework, a logic based revision paradigm, offers a sound and rigorous method of updating an agent’s beliefs of users’ information needs. This article examines the issues of applying the AGM belief revision framework to adaptive information filtering.
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Lau, R., ter Hofstede, A.H.M., Bruza, P.D. (1999). A Study of Belief Revision in the Context of Adaptive Information Filtering. In: Hui, L.C.K., Lee, DL. (eds) Internet Applications. ICSC 1999. Lecture Notes in Computer Science, vol 1749. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-46652-9_1
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DOI: https://doi.org/10.1007/978-3-540-46652-9_1
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