Context-Aware Recommendation by Aggregating User Context

Abstract

Traditional recommendation approaches do not consider the changes of user preferences according to context. As a result, these approaches consider the user’s overall preferences, although the user preferences on items varies according to his/her context. However, in our context-aware approach, we take into account not only user preferences, but also context information. Our approach can be easily adopted for content-based and collaborative filtering based recommendations. To exploit raw context information in recommendation, we abstract the raw context information to a concept level. Moreover, by aggregating the context information, we can improve the quality of recommendation. The results of several experiments show that our method is more precise than the traditional recommendation approaches.