Hierarchical naive bayes models for representing user profiles
暂无分享,去创建一个
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.
[1] Thomas D. Nielsen,et al. Classification using Hierarchical Naïve Bayes models , 2006, Machine Learning.
[2] Jonathan L. Herlocker,et al. Evaluating collaborative filtering recommender systems , 2004, TOIS.
[3] Paul Resnick,et al. Recommender systems , 1997, CACM.
[4] Pedro M. Domingos,et al. On the Optimality of the Simple Bayesian Classifier under Zero-One Loss , 1997, Machine Learning.