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现代图书情报技术  2012, Vol. 28 Issue (6): 54-59    DOI: 10.11925/infotech.1003-3513.2012.06.09
  情报分析与研究 本期目录 | 过刊浏览 | 高级检索 |
融合社会网络的协同过滤推荐算法研究
俞琰1,2, 邱广华1,3
1. 南京航空航天大学经济管理学院 南京 210016;
2. 东南大学成贤学院计算机系 南京 210088;
3. 美国宾州州立大学信息科学系 马尔文 19355
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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摘要 针对传统协同过滤推荐算法的数据稀疏性及恶意行为等问题,提出一种新的基于社会网络的协同过滤推荐算法。该算法借助社会网络信息,结合用户信任和用户兴趣,寻找目标用户最近邻居,并以此作为权重,形成项目推荐,以提高推荐的准确度。实验表明,相对于传统的协同过滤算法,该算法可有效缓解稀疏性及恶意行为带来的问题,显著提高推荐系统的推荐质量。
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俞琰
邱广华
关键词 协同过滤社会网络重启动随机游走    
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
收稿日期: 2012-03-05     
: 

TP393

 
引用本文:   
俞琰, 邱广华. 融合社会网络的协同过滤推荐算法研究[J]. 现代图书情报技术, 2012, 28(6): 54-59.
Yu Yan, Qiu Guanghua. Research on Collaborative Filtering Recommendation Algorithm by Fusing Social Network. New Technology of Library and Information Service, DOI:10.11925/infotech.1003-3513.2012.06.09.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2012.06.09
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