Authors:
Charif Haydar
;
Anne Boyer
and
Azim Roussanaly
Affiliation:
University Nancy 2, France
Keyword(s):
Recommender Systems, Trust, Reputation, Users Similarity.
Related
Ontology
Subjects/Areas/Topics:
Communities of Interest
;
e-Business and e-Commerce
;
Enterprise Information Systems
;
Social and Legal Issues
;
Social Networks and Organizational Culture
;
Society, e-Business and e-Government
;
Software Agents and Internet Computing
;
Web 2.0 and Social Networking Controls
;
Web Information Systems and Technologies
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, 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.