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| Mass Diffusion Recommendation Algorithm Based on Multi-Subnet Composited Complex Network Model |
| ZHOU Shuang, BIN Sheng, SHAO Fengjing, SUN Gengxin
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| School of data science and software engineering, Qingdao University, Qingdao 266071, China |
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Abstract Social recommendation algorithm based on social network is a popular method in recommendation system at present. However, there are many relationships among users in real social networks, and each relationship has different effects on recommendation. Therefore, the introduction of a social relationship in recommendation will inevitably affect the accuracy of recommendation results. In this paper, based on the multi-subnet composited complex network model, a multi-relationship composited network is constructed on the user-item bipartite graph, and a mass diffusion recommendation algorithm based on multi-relationship composited network is proposed. The experimental results on the real datasets Epinions and FilmTrust show that the recommendation algorithm with two kinds of social relationships is better than the recommendation algorithm with one kind of social relationship and traditional mass diffusion algorithm in the accuracy of recommendation.
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Published: 16 May 2019
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