Abstract
This work describes a multiagent recommender system where agents work on behalf of members of a group of customers, trying to reach the best recommendation for the whole group. The goal is to model the group recommendation as a distributed constraint optimization problem, taking customer preferences into account and searching for the best solution. Experimental results show that this approach can be sucessfully applied to propose recommendations to a group of users.
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Lorenzi, F., dos Santos, F., Ferreira, P.R., Bazzan, A.L.C. (2008). Optimizing Preferences within Groups: A Case Study on Travel Recommendation. In: Zaverucha, G., da Costa, A.L. (eds) Advances in Artificial Intelligence - SBIA 2008. SBIA 2008. Lecture Notes in Computer Science(), vol 5249. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88190-2_16
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DOI: https://doi.org/10.1007/978-3-540-88190-2_16
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