Détection de communautés d'intérêt et recommandation sociale par leaders
Identifieur interne : 000096 ( PascalFrancis/Checkpoint ); précédent : 000095; suivant : 000097Détection de communautés d'intérêt et recommandation sociale par leaders
Auteurs : Armelle Brun [France] ; Anne Boyer [France]Source :
- Ingénierie des systèmes d'information : (2001) [ 1633-1311 ] ; 2012.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Recommandation, Intérêt.
English descriptors
- KwdEn :
Abstract
Recommender Systems aim at increasing the users' satisfaction in an online service, by suggesting items that correspond to their preferences. In this article we aim at increasing the quality of the recommendations, as well as reducing the size of the recommendation model. To increase the quality of recommendations, we propose a new way to form communities of interest, by exploiting the ratio between the similarity within communities and the similarity outside of the communities. To reduce the size of the recommendation model, we propose to select a subset of users, the leaders. We show that the new algorithm used to build communities leads to an improvement of the recommendations and that the leader-based recommender decreases the size of the model by 80%, while maintaining a high coverage and accuracy.
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Pascal:13-0100266Le document en format XML
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