A Trust Network-based Collaborative Filtering Recommendation Strategy
Yan Tang · Journal of Southwest China Normal University · 2008
Collaborative Filtering(CF) is one of the most prevalent recommendation approaches.It provides users with personalized services according to similarity of their preferences.However,the performance of traditional CF method is seriously limited due to the Sparsity problem.A new approach is proposed to deal with this problem.It introduces trust network in traditional CF process.Trust value is propagated through the trust network to match more neighbors for cold start users,and is combined with similarity to generate a compound weight to produce recommendations.Experiment shows that this method is more effective than traditional CF obviously.