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基于SVD++与行为分析的社交推荐 被引量：4

Social recommendation based on SVD + + and behavior analysis
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摘要 社交网络和推荐系统作为当前学术界和工业界的研究热点,二者的结合是大势所趋。然而当前的研究主要集中于用户兴趣建模,对行为的分析建模相对较少,因此提出多种方法对用户行为进行分析与建模,并与SVD++模型进行融合,实验结果证实了方法的有效性。 As the hot research topic in both academia and industry, the combination of social networks and recommender system is a major trend. However, current research is mainly focused on modeling user interests while behavior analysis and modeling is relatively scarce. Thus several methods for user behavior analysis and modeling were proposed in this paper and then combined with the SVD ＋ ＋ model. Experiments demonstrate the effectiveness of the methodology described.
作者 刘剑波 杨健
机构地区 南京理工大学计算机科学与工程学院
出处 《计算机应用》 CSCD 北大核心 2013年第A01期82-86,共5页 journal of Computer Applications
关键词 推荐系统 社交网络 矩阵分解 排序学习 行为分析 recommender system social network matrix factorization learning to rank behavior analysis
分类号 TP393.027 [自动化与计算机技术—计算机应用技术] TP181 [自动化与计算机技术—控制理论与控制工程]
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参考文献15

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二级参考文献5

共引文献23

同被引文献20

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计算机应用
2013年 第A01期

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