Abstract
Finding the right material on the Web could be a worthwhile result. Users waste too much time to discover the useful information. Recommender system can provide some shortcuts to the user, but if the recommendation is based on people’s opinion, one question remains — how relevant is a user’s opinion? This paper presents a model to define the user’s relevance opinion in a recommender system. This metric aims to help the target user to decide in what recommendation he should focus his attention. Beyond the model, we present a real experiment using an e-government database.
This research has been funded in part by the Brazilian agency CAPES under grant BEX1357/03-4.
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© 2005 Springer-Verlag Berlin Heidelberg
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Cazella, S.C., Alvares, L.O.C. (2005). Modeling User’s Opinion Relevance to Recommending Research Papers. In: Ardissono, L., Brna, P., Mitrovic, A. (eds) User Modeling 2005. UM 2005. Lecture Notes in Computer Science(), vol 3538. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527886_42
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DOI: https://doi.org/10.1007/11527886_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27885-6
Online ISBN: 978-3-540-31878-1
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