Abstract
Algorithms designed to support users in retrieving relevant information base their relevance computations on user profiles, in which representations of the users interests are maintained. This paper focuses on the use of supervised machine learning techniques to induce user profiles for Intelligent Information Access. The access must be personalized by profiles allowing users to retrieve information on the basis of conceptual content. To address this issue, we propose a method to learn sense-based user profiles based on WordNet, a lexical database.
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Semeraro, G., Lops, P., Degemmis, M., Niederée, C., Stewart, A. (2005). Exploiting Lexical Knowledge in Learning User Profiles for Intelligent Information Access to Digital Collections. In: Fox, E.A., Neuhold, E.J., Premsmit, P., Wuwongse, V. (eds) Digital Libraries: Implementing Strategies and Sharing Experiences. ICADL 2005. Lecture Notes in Computer Science, vol 3815. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11599517_29
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DOI: https://doi.org/10.1007/11599517_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30850-8
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