Abstract
In this paper we present an Information Filtering system of HTML/Text documents collected from the World Wide Web (WWW), based on a representation of user interests as inferred by the system through a dialogue. One of the distinguishing features of the system is the use of a hybrid approach to user modeling, in which case-based components and an artificial neural network are integrated into one coherent system. Moreover, in order to perform an accurate filtering, the system takes advantage of semantic networks and a well-structured database. The results of the first experiments with the system are very encouraging.
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© 1997 Springer-Verlag Wien
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Ambrosini, L., Cirillo, V., Micarelli, A. (1997). A Hybrid Architecture for User-Adapted Information Filtering on the World Wide Web. In: Jameson, A., Paris, C., Tasso, C. (eds) User Modeling. International Centre for Mechanical Sciences, vol 383. Springer, Vienna. https://doi.org/10.1007/978-3-7091-2670-7_8
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DOI: https://doi.org/10.1007/978-3-7091-2670-7_8
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82906-6
Online ISBN: 978-3-7091-2670-7
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