A Clustering Approach for Collaborative Filtering Recommendation Using Social Network Analysis

作者：Pham Manh Cuong^*; Cao Yiwei; Klamma Ralf; Jarke Matthias

来源：Journal of Universal Computer Science, 2011, 17(4): 583-604.

• clustering
• collaborative filtering
• trust
• social network analysis

Collaborative Filtering(CF) is a well-known technique in recommender systems. CF exploits relationships between users and recommends items to the active user according to the ratings of his/her neighbors. CF suffers from the data sparsity problem, where users only rate a small set of items. That makes the computation of similarity between users imprecise and consequently reduces the accuracy of CF algorithms. In this article, we propose a clustering approach based on the social information of users to derive the recommendations. We study the application of this approach in two application scenarios: academic venue recommendation based on collaboration information and trust-based recommendation. Using the data from DBLP digital library and Epinion, the evaluation shows that our clustering technique based CF performs better than traditional CF algorithms.

• 出版日期2011