Abstract
A systems approach to the automatic and adaptive personalization of Internet news is described. Implemented on the client side as a lightweight, transparent software system, this approach is based on implicit user feedback, thereby preserving privacy while avoiding the constant recustomization needed in explicit schemes. The system consists of two modules: (1) a profiling agent, which unobtrusively monitors news reading patterns to track interest in different topics while acting as a proxy server on the user’s computer; (2) and an action agent, which uses the profile information to retrieve, filter, and present news articles. A prototype of the system was implemented and evaluated over a two week period. Precisions (the percentages of relevant articles returned by the system) ranging from 60-95% were observed for profiles representing various combinations of interests. The system also responded very well to simulated changes in user interests, returning rapidly increasing numbers of articles relevant to newly developed interests.
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Sunderam, A.V. (2002). Automated Personalization of Internet News. In: De Bra, P., Brusilovsky, P., Conejo, R. (eds) Adaptive Hypermedia and Adaptive Web-Based Systems. AH 2002. Lecture Notes in Computer Science, vol 2347. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47952-X_36
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DOI: https://doi.org/10.1007/3-540-47952-X_36
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