Trust in recommender systems

John O'Donovan, Barry Smyth
2005 Proceedings of the 10th international conference on Intelligent user interfaces - IUI '05  
Recommender systems have proven to be an important response to the information overload problem, by providing users with more proactive and personalized information services. And collaborative filtering techniques have proven to be an vital component of many such recommender systems as they facilitate the generation of high-quality recommendations by leveraging the preferences of communities of similar users. In this paper we suggest that the traditional emphasis on user similarity may be
more » ... ated. We argue that additional factors have an important role to play in guiding recommendation. Specifically we propose that the trustworthiness of users must be an important consideration. We present two computational models of trust and show how they can be readily incorporated into standard collaborative filtering frameworks in a variety of ways. We also show how these trust models can lead to improved predictive accuracy during recommendation.
doi:10.1145/1040830.1040870 dblp:conf/iui/ODonovanS05 fatcat:etxkucqx5zdytpfb2ok5v6gmgy