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 / Panniello, Umberto; Gorgoglione, Michele. - ELETTRONICO. - 771:(2011). (Intervento presentato al convegno 5th International Workshop on New Challenges in Distributed Information Filtering and Retrieval, DART 2011 tenutosi a Palermo, Italy nel September 17, 2011).
Context-Aware Recommender Systems: A Comparison Of Three Approaches
Umberto Panniello;Michele Gorgoglione
2011-01-01
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 betterI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.