| 一种基于三部图网络的协同过滤算法 |
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| 引用本文： | 陈超,张颖超,缪进.一种基于三部图网络的协同过滤算法[J].南京气象学院学报,2010(4):337-339. |
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| 作者姓名： | 陈超 张颖超 缪进 |
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| 作者单位： | 1，南京信息工程大学 信息与控制学院 |
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| 基金项目： | 江苏省“六大人才高峰”项目 |
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| 摘 要： | 推荐系统是电子商务领域最重要的技术之一,而协同过滤算法又是推荐系统用得最广泛的.提出了一种基于加权三部图网络的协同过滤算法,用户、产品及标签都被考虑到算法中,并且研究了标签结点的度对用户相似性计算的影响.实验结果表明,此算法在解决用户冷启动问题的同时,还具有较高的推荐准确性.
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| 关 键 词： | 推荐系统 协同过滤 二部图网络 三部图网络 相似性 |
A collaborative filtering recommender algorithm based on tripartite network |
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| chenchao zhangyingchao miaojin.A collaborative filtering recommender algorithm based on tripartite network[J].Journal of Nanjing Institute of Meteorology,2010(4):337-339. |
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| Authors: | chenchao zhangyingchao miaojin |
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| Institution: | 1 School of Information & Cybernetics; Nanjing University of Information Science & Technology; Nanjing 210044; |
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| Abstract: | Recommender system is one of the most important technologies in E-commerce,and the collaborative filtering algorithm is the most widely used technique in recommender system.In this paper,we proposed a collaborative filtering algorithm based on weighted tripartite network,which takes users,items and tags into account,and we also studied the degree of tags which may affect the user-user similarity computation.The experimental results demonstrate that the algorithm can solve the cold start problem with high re... |
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| Keywords: | recommender system collaborative filtering bipartite network tripartite network similarity |
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