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Context-Aware Recommender Systems: A Comparison Of Three Approaches

Methods for generating context-aware recommendations were classified into the pre-filtering, post-filtering and contextual modeling approaches. This paper proposes a novel type of contextual modeling, that is called contextual neighbors, based on the idea of using context to compute the neighborhood in a collaborative filtering approach, and introduces four variants of this method. In addition, the paper presents the results of the comparison among these four approaches and among the contextual neighbors approach to the other contextual approaches and to the un-contextual one. While some of these methods have been studied independently, few prior research has compared their performance to determine which of them is better.