Séminaire (organisé par l’équipe de recherche DI)

Shameem A Puthiya Parambath

Doctorant, laboratoire Heudiasyc


A Coverage-Based Approach to Recommendation Diversity On Similarity Graph


Mardi 13 septembre 2016 à 14 h en salle GI016 (Bâtiment Blaise Pascal)

Résumé :

We consider the problem of generating diverse, personalized recommendations such that a small set of recommended items covers a broad range of the user’s interests. We represent items in a similarity graph, and we formulate the relevance/diversity trade-off as finding a small set of unrated items that best covers a subset of items positively rated by the user. In contrast to previous approaches, our method does not rely on an explicit trade-off between a relevance objective and a diversity objective, as the estimations of relevance and diversity are implicit in the coverage criterion. We show on several benchmark datasets that our approach compares favorably to the state-of-the-art diversification methods according to various relevance and diversity measures.



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FR SHIC 3272

Collegium UTC/CNRS