|Table of Contents|

A Recommendation Algorithm Based on Network Link Prediction(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2015年01期
Page:
75-
Research Field:
计算机科学
Publishing date:

Info

Title:
A Recommendation Algorithm Based on Network Link Prediction
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)
Keywords:
weighted bipartite network; link prediction; similarity; recommendation algorithm
PACS:
TP311
DOI:
-
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.

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.

Memo

Memo:
-
Last Update: 2015-03-30