Methods for generating context-aware recommendations were classified into the pre-filtering, post-filtering and contextual modeling approaches. This pa-per proposes a novel type of contextual modeling, that is called contextual neigh-bors, based on the idea of using context to compute the neighborhood in a colla-borative filtering approach, and introduces four variants of this method. In addition, the paper presents the results of the comparison among these four ap-proaches 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 de-termine which of them is better

Context-Aware Recommender Systems: A Comparison Of Three Approaches

Umberto Panniello;Michele Gorgoglione
2011

Abstract

Methods for generating context-aware recommendations were classified into the pre-filtering, post-filtering and contextual modeling approaches. This pa-per proposes a novel type of contextual modeling, that is called contextual neigh-bors, based on the idea of using context to compute the neighborhood in a colla-borative filtering approach, and introduces four variants of this method. In addition, the paper presents the results of the comparison among these four ap-proaches 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 de-termine which of them is better
5th International Workshop on New Challenges in Distributed Information Filtering and Retrieval, DART 2011
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11589/16567
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