[1]华秋云,陈 崚.基于网络链接预测的推荐算法[J].南京师大学报(自然科学版),2015,38(01):75.
　Hua Qiuyun,Chen Ling.A Recommendation Algorithm Based on Network Link Prediction[J].Journal of Nanjing Normal University(Natural Science Edition),2015,38(01):75.
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基于网络链接预测的推荐算法()
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《南京师大学报》（自然科学版）[ISSN:1001-4616/CN:32-1239/N]

卷:
第38卷
期数:
2015年01期
页码:
75
栏目:
计算机科学
出版日期:
2015-06-30

文章信息/Info

Title:
A Recommendation Algorithm Based on Network Link Prediction
作者:
华秋云1; 陈 崚1; 2
(1.扬州大学信息学院计算机系,江苏 扬州 225009)(2.南京大学软件新技术国家重点实验室,江苏 南京 210093)
Author(s):
Hua Qiuyun1; Chen Ling1; 2
(1.Department of Computer Science,Information Institute,Yangzhou University,Yangzhou 225009,China)(2.State Key Lab of Novel Software Tech,Nanjing University,Nanjing 210093,China)
关键词:
带权二部网络; 链接预测; 相似性; 推荐算法
Keywords:
weighted bipartite network; link prediction; similarity; recommendation algorithm
分类号:
TP311
文献标志码:
A
摘要:
提出基于二部网络连接预测的推荐算法. 将用户-项目的评分矩阵用带权的二部网络来表达,根据推荐问题和带权二部网络连接预测问题的相似性将推荐问题抽象为二部网络上的链接预测问题,采用基于相似度的连接预测算法进行项目推荐. 算法综合考虑了顶点间的拓扑关系,以及用户之间、项目之间的相似性,找出用户对其尚未表达的项目的潜在兴趣度,应用二部网络连接预测的算法来解决推荐问题. 实验结果表明,算法能够有效地提高推荐的精度.
Abstract:
An algorithm for recommendation based on link prediction in a bipartite network is presented. We use a weighted bipartite network to represent the user-item matrix. Due to the similarity between recommendation and link prediction in bipartite network,we transform the recommendation into the problem of link prediction in bipartite network. The similarity based method is used to predict the potential links considering the topological similarity between the nodes in the network,the similarity between users and the similarity between the items. The potential interests of the users to the items can be found by link prediction in the bipartite network. Our experimental results show that our algorithm can get high recommendation results.

参考文献/References:

[1] 刘建国,周涛,汪秉宏. 个性化推荐系统的研究进展[J]. 自然科学进展,2009,19(1):1-15.
[2]Schafer B,Konstan J A. E-commerce recommendation applications[EB/OL]. http://citeseer.nj.nec.com,2010,5(1):115-153.
[3]Mobasher B,Dai H,Luo I,et al. Discovery of aggregate usage profiles for web personalization[C]//Proceedings of the Web KDD Workshop on Web Mining for E-commerce-Challenges and Opportunnities.NY,2000,4(1):1-11.
[4]许海玲,吴潇,李晓东,等. 互联网推荐系统比较研究[J]. 软件学报,2009,20(2):1-10.
[5]LI J,XU Y,WANG Y F,et al. Strongest association rules mining for efficient applications[C]//Proceedings of the Fourth IEEE Conference on Service Systems and Service Management. Piscataway:IEEE Press,2007:502-507.
[6]李杰,徐勇,王云峰,等. 面向个性化推荐的强关联规则挖掘[J]. 系统工程理论与实践,2009,29(8):144-152.
[7]Wang F H,Jian S Y. An effective content-based recommendation method for Web browsing based on keyword context matching[J]. Journal of Informatics and Electronics,2006,1(2):49-59.
[8]Wartena C,Slakhorst W,Wibbels M,et al. Selecting keywords for content based recommendation[C]//CIKM’10:Proceedings of the 19th ACM International Conference on Information and Knowledge Management. New York:ACM Press,2010:1 533-1 536.
[9]Herlocker J L,Konstan J A,Terveen L G,et al. Evaluating collaborative filtering recommender systems[J]. ACM Transactions on Information Systems,2004,22(1):5-53.
[10]Chen Y L,Cheng L C. A novel collaborative filtering approach for recommending ranked items[J]. Expert Systems with Applications,2008,34(4):2 396-2 405.
[11]张新猛,蒋盛益. 基于加权二部图的个性化推荐算法[J]. 计算机应用,2012,32(3):654-657.
[12]Zhou Tao,Ren Jie,Medo M,et al. Bipartite network projection and personal recommendation[J]. Physical Review E,2007,76(4):046115.
[13]Liu Jianguo,Wang Binghong,Guo Qiang. Improved collaborative filtering algorithm via information transformation[J]. International Journal of Modern Physics C,2009,20(2):285-293.
[14]王茜,段双艳. 一种改进的基于二部图网络结构的推荐算法[J]. 计算机应用研究,2013,33(3):771-774.
[15]Getoor L,Diefl C P. Link mining:a survey[J]. ACM SIGKDD Explorations Newsletter,2005,7(2):3-12.
[16]Lü Linyuan. Link prediction on complex networks[J]. Journal of University of Electronic Science and Technology of China,2010(9):5-39.
[17]姜波,张晓筱,潘伟丰,等. 基于二部图的服务推荐算法研究[J]. 华中科技大学学报,2013,12:93-99.
[18]Newman M. The structure and function of complex networks[J]. SIAM Review,2003,45(2):167-256.
[19]Liben-Nowell D,Kleinberg J. The link-prediction problem for social networks[J]. J Am Soc Inform Sci Technol,2007,58(7):1 019-1 031.
[20]He Yinhui,Chen Duanbing. Similarity algorithm based on users common neighbors and grade information[J]. Computer Science,2010(9):184-187.

备注/Memo

备注/Memo:
收稿日期:2014-08-16.
基金项目:国家自然科学基金(61379066、61070047,61379064)、江苏省自然科学基金(BK20130452、BK2012672、BK2012128)、江苏省教育厅自然科学基金(12KJB520019、13KJB520026、09KJB20013).
通讯联系人:陈崚,教授,博士生导师,研究方向:并行计算、数据挖掘、计算机软件、人工智能、蚁群算法等. E-mail:yzulchen@163.com
更新日期/Last Update: 2015-03-30