Trust-aware recommender systems
Proceedings of the 2007 ACM conference on Recommender systems
SoRec: social recommendation using probabilistic matrix factorization
Proceedings of the 17th ACM conference on Information and knowledge management
Learning to recommend with social trust ensemble
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Trust based recommender system for the semantic web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Recommender systems with social regularization
Proceedings of the fourth ACM international conference on Web search and data mining
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Recommender systems with social networks (RSSN) have been well studied in recent works. However, these methods ignore the relationships among items, which may affect the quality of recommendations. Motivated by the observation that related items often have similar ratings, we propose a framework integrating items' relations, users' social graph and user-item rating matrix for recommendation. Experimental results show that our approach performs better than the state-of-art algorithm and the method with only users' social graph ensemble in terms of MAP and RMSE.