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浙江大学学报(工学版)
浙江大学学报(工学版)
计算机技术     
基于社交关系拓扑结构的冷启动推荐方法
张亚楠, 曲明成,刘宇鹏
1.哈尔滨理工大学 软件学院,黑龙江 哈尔滨 150040；2.哈尔滨工业大学 计算机科学与技术学院,黑龙江 哈尔滨 150001
Recommendation method based on social topology for cold start users
ZHANG Ya nan,QU Ming cheng,LIU Yu peng
1. Software school,Harbin University of Science and Technology,Harbin 150040,China；
2. School of computer science and Technology, Harbin Institute of Technology,Harbin 150001, China
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摘要：

针对冷启动用户仅有很少行为信息,很难为冷启动用户给出推荐的问题,提出基于比较社交网络中用户间社交关系拓扑结构的冷启动推荐方法.社交网络中包含多种可以反映用户偏好的社交关系,然而现有基于社交网络的冷启动推荐研究仅利用一种或者很少的社交关系,没有充分利用社交网络中的多种社交关系,很少考虑融合相异的社交关系,限制了在实际环境中对冷启动用户的推荐效果.由于社交关系在社交网络中的权重越大在推荐中的影响越大,为了给出准确的冷启动推荐,提出基于社交关系拓扑的相似用户发现方法(STSUM),基于最大熵原理融合社交网络中多种相异的社交关系,基于图形模式匹配为冷启动用户发现相似用户,给出推荐.在真实的网站中提取社交关系和用户数据,实验结果表明,STSUM可以有效地提高对冷启动用户的推荐效果且需要较少的训练集．
Abstract:

It is very difficult to give recommendations for coldstart user who usually has very sparse historical behavior records. A coldstart recommendation method was proposed based on comparison of topology of social relationships in social networks  to improve recommendation effectiveness for coldstart user.  Social network contains many social relationships which could reflect users preference. However, most of existing social network based recommendation methods use only one or a few social relationships of social network, which do not make full use of multiple social relationships; rarely consider how to merge dissimilar social relationships, and could not give satisfactory recommendation in actual environment. In social network the higher weight a kind of social relationship takes, the greater right of recommendations it will have. In order to give accurate recommendations for coldstart user,  a social topology based similar user matching method (STSUM) was proposed, Maximum entropy principle was introduced  to merge multiple social relationships, and graph pattern matching was used to find similar users for coldstart user. Then  recommendations were given according to similar users records. Social relationship and user data from a real website to show the recommendation effectiveness of STSUM. The experimental results show that STSUM con give accurate recommendations for coldstart user and needs a few training set．
出版日期: 2017-01-14
:     
基金资助:

国家自然科学基金青年基金资助项目（61300115）.
作者简介: 张亚楠(1981-), 男, 讲师,从事社交网络推荐等研究.ORCID: 000000020633826X E-mail: ynzhang_1981@163.com
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张亚楠, 曲明成,刘宇鹏. 基于社交关系拓扑结构的冷启动推荐方法[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008973X.2016.05.026.

ZHANG Ya nan,QU Ming cheng,LIU Yu peng. Recommendation method based on social topology for cold start users. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008973X.2016.05.026.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008973X.2016.05.026    或    http://www.zjujournals.com/eng/CN/Y2016/V50/I5/1001

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