Acquiring user preferences for information filtering in interactive multi-media services

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Abstract

The increasing availability of a large number of interactive multi-media information services means that users have a large and diverse collection of choices open to them. One method of assisting users to navigate through this large collection is to use information filtering to extract only the information relevant to an end-user according to his/her long-term preferences. In this paper, we describe a mechanism to acquire a user's long-term preferences (user profile), and then show how the acquired profile may be used to suggest selections that may be of interest to the user. The profile is acquired on the basis of a user's habits using a Heuristic-Statistical approach, and is used to create selection indices. Our mechanism has been incorporated into an experimental Video On Demand service that is implemented using a client-server architecture.

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Raskutti, B., & Beitz, A. (1996). Acquiring user preferences for information filtering in interactive multi-media services. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1114, pp. 47–58). Springer Verlag. https://doi.org/10.1007/3-540-61532-6_5

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