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New Technology of Library and Information Service  2012, Vol. 28 Issue (6): 54-59    DOI: 10.11925/infotech.1003-3513.2012.06.09
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Research on Collaborative Filtering Recommendation Algorithm by Fusing Social Network
Yu Yan1,2, Qiu Guanghua1,3
1. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
2. Computer Science Department, Southeast University Chengxian College, Nanjing 210088, China;
3. Information Science Department, Pennsylvania State University, Malvern 19355, USA
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Abstract  Aiming at data sparsity and malicious behavior in traditional collaborative filtering algorithm, this paper presents a new algorithm of collaborative filtering based on social network. Depending on social network information, the algorithm integrates user’s trust and preference in order to find the nearest neighbors of the target user, which the algorithm uses to compute weight of neighbors and to form item recommendation. Experimental results show that the algorithm can alleviate the sparsity and malicious behaviors problems and achieve a better prediction accuracy than traditional collaborative filtering algorithms.
Key wordsCollaborative filtering      Social network      Random walk with restart     
Received: 05 March 2012      Published: 30 August 2012



Cite this article:

Yu Yan, Qiu Guanghua. Research on Collaborative Filtering Recommendation Algorithm by Fusing Social Network. New Technology of Library and Information Service, 2012, 28(6): 54-59.

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