Personalized Recommendation Algorithm of Social NetworkBased on Global Similarity
摘要
Aiming at the problem of neglecting project similarity information in classical social network recommendation algorithm,an improved personalized recommendation algorithm for social network is proposed. The global project similarity information between projects is mined,and the reliability of trust values among social network users is analyzed,and the two are combined in a model to realize personalized recommendation to users. Experimental results on Filmtrust datasets and Ciao datasets show that,compared with PMF,SocialMF and SoRec algorithms,this algorithm can improve the accuracy of recommendation and reduce the recommendation error in cold start problem.
引用本文（GB/T 7714）
ZHANG Yihao,LI Liang,ZHAO Qinghua,MA Jianfen,DUAN Qianqian. Personalized Recommendation Algorithm of Social NetworkBased on Global Similarity[J]. DOAJ (DOAJ: Directory of Open Access Journals), 2018.
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