Communications of the ACM
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Classification using Hierarchical Naïve Bayes models
Machine Learning
Personalization of Content Ranking in the Context of Local Search
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
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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.