Charif Haydar, Anne Boyer, Azim Roussanaly


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, and 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 both approaches in order to improve prediction accuracy and coverage.


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Paper Citation

in Harvard Style

Haydar C., Boyer A. and Roussanaly A. (2012). HYBRIDISING COLLABORATIVE FILTERING AND TRUST-AWARE RECOMMENDER SYSTEMS . In Proceedings of the 8th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-8565-08-2, pages 695-700. DOI: 10.5220/0003937406950700

in Bibtex Style

author={Charif Haydar and Anne Boyer and Azim Roussanaly},
booktitle={Proceedings of the 8th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},

in EndNote Style

JO - Proceedings of the 8th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
SN - 978-989-8565-08-2
AU - Haydar C.
AU - Boyer A.
AU - Roussanaly A.
PY - 2012
SP - 695
EP - 700
DO - 10.5220/0003937406950700