Jian Chen, Guanliang Chen, H. Zhang, Jin Huang, Gansen Zhao
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Social Recommendation Based on Multi-relational Analysis
Social recommendation methods, often taking only one kind of relationship in social network into consideration, still faces the data sparsity and cold-start user problems. This paper presents a novel recommendation method based on multi-relational analysis: first, combine different relation networks by applying optimal linear regression analysis, and then, based on the optimal network combination, put forward a recommendation algorithm combined with multi-relational social network. The experimental results on Epinions dataset indicate that, compared with existing algorithms, can effectively alleviate data sparsity as well as cold-start issues, and achieve better performance.