Preference-based Graphic Models for Collaborative Filtering

Collaborative filtering is a very useful general technique for exploiting the preference patterns of a group of users to predict the utility of items to a particular user. Previous research has studied several probabilistic graphic models for collaborative filtering with promising results. However, while these models have succeeded in capturing the similarity among users and items, none of them has considered the fact that users with similar interests on items can have very different rating patterns; some users tend to assign a higher rating to all items than other users. In this paper, we propose and study two new graphic models that address the distinction between user preferences and ratings. In one model, called the decoupled model, we introduce two different variables to decouple a user’s preferences from his/her ratings. In the other, called the preference model, we model the orderings of items preferred by a user, rather than the user’s numerical ratings of items. Empirical...

• Type: Conference
• Year: 2003
• Where: UAI
• Authors: Rong Jin, Luo Si, ChengXiang Zhai
• Keywords: Collaborative Filtering, Graphic Models, UAI 2003, UAI 2008, User Preferences