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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Alchourrón, C.E., Gärdenfors, P., Makinson, D.: On the logic of theory change: partial meet contraction and revision functions. Journal of Symbolic Logic 50, 510–530 (1985)
Amati, G., Georgatos, K.: Relevance as deduction: a Logical View of Information Retrieval. In: Crestani, F., Lalmas, M. (eds.) Proceedings of the Second Workshop on Information Retrieval, Uncertainty and Logic WIRUL 1996, pp. 21–26. University of Glasgow, Glasgow (1996), Technical Report TR-1996-29
Barwise, J.: The Situation in Logic. CSLI Lecture Note Series, vol. 17. CSLI, Stanford (1989)
Belkin, N., Croft, W.: Information Filtering and Information Retrieval: Two sides of the same coin? Communications of the ACM 35(12), 29–38 (1992)
Brooks, T.A.: People, Words and Perceptions: A Phenomenological Investigation of Textuality. American Society for Information Science 46(2), 103–115 (1995)
Bruza, P.D.: Intelligent Filtering using Nonmonotonic Inference. In: Proceedings of the 1st Australian Document Computing Symposium, Melbourne, Australia, pp. 1–7. Department of Computer Science, RMIT (1996)
Bruza, P.D., Huibers, T.W.C.: Investigating Aboutness Axioms Using Information Fields. In: Croft, W.B., van Rijsbergen, C.J. (eds.) Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Dublin, Ireland, pp. 112–121. Springer, Heidelberg (1994)
Bruza, P.D., van Linder, B.: Preferential Models of Query by Navigation. In: Crestani, F., Lalmas, M., van Rijsbergen, C.J. (eds.) Information Retrieval: Uncertainty and Logics. The Kluwer International Series on Information Retrieval, vol. 4, pp. 73–96. Kluwer Academic Publishers, Dordrecht (1998)
Gärdenfors, P.: Knowledge in flux: modeling the dynamics of epistemic states. The MIT Press, Cambridge (1988)
Gärdenfors, P.: Belief revision: An introduction. In: Gärdenfors, P. (ed.) Belief Revision, pp. 1–28. Cambridge University Press, Cambridge (1992)
Kirsch, S.: The future of Internet Search: Infoseek’s experiences searching the Internet. ACM SIGIR FORUM 32(2), 3–7 (1998)
van Rijsbergen, C.J.: Towards an Information Logic. In: Belkin, N.J., van Rijsbergen, C.J. (eds.) Proceedings of the 12th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Cambridge, Massachusetts, pp. 77–86. ACM Press, New York (1989)
Rocchio, J.: Relevance Feedback in Information Retrieval. In: Salton, G. (ed.) The SMART retrieval system: experiments in automatic document processing, pp. 313–323. Prentice-Hall, Englewood Cliffs (1971)
Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill, New York (1983)
Wooldridge, M., Jennings, N.: Intelligent Agents: Theory and Practice. Knowledge Engineering Review 10(2), 115–152 (1995)
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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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