Hybridising collaborative filtering and trust-aware recommender systems

Charif Haydar 1 Anne Boyer 1 Azim Roussanaly 1, *
* Auteur correspondant
1 KIWI - Knowledge Information and Web Intelligence
LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Recommender systems (RS) aim to predict items that users would appreciate, over a list of items. In evaluation of recommender systems, two issues can be defined: accuracy of prediction which implies the satisfaction of the user, coverage which implies the percentage of satisfied users. Collaborative filtering (CF) is the master approach in this domain, but still has some weaknesses especially about coverage. Trust-aware approach is today another promising approach in RS within social environments, whose prediction exceeds the quality of (CF). In this paper we propose several strategies to hybridize those both approaches in order to improve prediction quality, in the term of accuracy and coverage.
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Communication dans un congrès
8th International Conference on Web Information Systems and Technologies -WEBIST'2012, Apr 2012, Porto, Portugal. 2012
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Charif Haydar, Anne Boyer, Azim Roussanaly. Hybridising collaborative filtering and trust-aware recommender systems. 8th International Conference on Web Information Systems and Technologies -WEBIST'2012, Apr 2012, Porto, Portugal. 2012. 〈hal-00679233〉

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