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SIGIR
2008
ACM

Hierarchical naive bayes models for representing user profiles

8 years 9 months ago
Hierarchical naive bayes models for representing user profiles
In this paper, we show how a user profile can be enhanced when a more detailed description of the products is included. Two main assumptions have been considered: the first implies that the set of features used to describe an item can be organized into a well-defined set of components or categories, and the second is that the user's rating for a given item is obtained by combining user opinions of the relevance of each component. Categories and Subject Descriptors H.3 [Information Storage and Retrieval] General Terms Algorithms Keywords Probabilistic Reasoning, Recommender System, Recommender Systems, Learning User Profiles
Juan F. Huete, Luis M. de Campos, Juan M. Fern&aac
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where SIGIR
Authors Juan F. Huete, Luis M. de Campos, Juan M. Fernández-Luna, Miguel A. Rueda-Morales
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