Computer Science ›› 2016, Vol. 43 ›› Issue (7): 259-264.doi: 10.11896/j.issn.1002-137X.2016.07.047

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Weighted Bipartite Network Recommendation Algorithm Based on Increasing Similarity Coefficient

LI Zhen-dong, LUO Qi and SHI Li-li   

  • Online:2018-12-01 Published:2018-12-01

Abstract: The recommendation algorithm based on bipartite networks is a research hotspot in the personalized recommendation system,while the difficulty of research is how to make use of the users’ evaluation resources scientifically to work out an efficient and accurate recommendation for target users in the absence of rating data.Meanwhile,it has received sufficient attention of scholars.Therefore,a new recommendation algorithm was put forward with the monotonous saturation function as weight,and tangent of target users and other projects’ common rating numbers against the mean value of total users is used as traditional similarity coefficient.At the same time,after the coefficient gets adjusted,the similarity will be sorted in descending order,the set of the first K nearest neighbors of which can be utilized for target users’ recommendation.The experimental results prove that the revised algorithm improves the accuracy of re-commendation and reduces its complexity.

Key words: Personalized recommendation,Weighted bipartite networks,Monotonic saturation,Accuracy

[1] Xu H L,Wu X,Li X D,et al.Comparison study of Internet re- commendation system[J].Journal of Software,2009,0(2):1-10(in Chinese) 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
[2] Schafer J B,Konstan J,Riedl J.Recommender systems in E-commerce[C]∥Proc of E-COMMERCE.1999:158-166
[3] Liu J G,Zhou T,Wang B H.Research progress of personalized recommendation system[J].Progress in Natural Science,2009,9(1):1-12(in Chinese) 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,2009,9(1):1-12
[4] 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
[5] Wartena C,Slakhorst W,Wibbels M,et al.Selecting keywords for content based recommendation[C]∥Proceedings of the 19th ACM Intemational Conference on Information and Knowledge Management(CIKM 10).New York:ACM Press,2010:1533-1536
[6] Herlocker J L,Konstan J A,Terveen L G,et al.Evaluaing collaborative filtering recommender systems[J].ACM Transactions on Information Systems,2004,22(1):5-33
[7] Chen Y L,Cheng L C.A novel collaborative filtering approach for recommending ranked items[J].Expert Systems with Applications,2008,34(4):2396-2405
[8] Hong W X,Weng Y,Zhu S Z.Hybrid recommender system for vertical e-commerce website[J].System Engineering Theory & Pratice,2010,30(5):928-935(in Chinese) 洪文兴,翁洋,朱顺痣.垂直电子商务网站的混合型推荐系统[J].系统工程理论与实践,2010,30(5):928-935
[9] Zhou Tao,Ren Jie,Medo M,et al.Bipartite network projection and personal recommendation[J].Physical Review E,2007,76(4):04115
[10] Liu Jian-guo,Wang Bing-hong,Guo Qiang.Improved collaborative filtering algorithm via information transformation[J].International Journal of Modern Physics C,2009,20(2):285-293
[11] Huang Z,Chen H,Zeng D.Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering[J].ACM Transactions on Information Systems,2004,22(1):116-142
[12] Zhang X M,Jiang S Y.Personalized recommendation algorithm based on weighted bipartite network[J].Journal of Computer Applications,2012,2(3):654-658(in Chinese) 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):654-658
[13] Wang Q,Duan S Y.Improved recommendation algorithm based on bipartite networks[J].Application Research of Computers,2013,0(3):771-774 (in Chinese) 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,2013,30(3):771-774
[14] Tao W A,Fan H L.Collaborative filtering recommendation algorithm based on nearest-neighborhood and rating support[J].Application Research of Computers,2012,29(5):1723-1725,1728(in Chinese) 陶维安,范会联.基于评分支持度的最近邻协同过滤推荐算法[J].计算机应用研究,2012,29(5):1723-1725,1728
[15] Ansari,Essegaier A S,Kohli R .Internet recommendation systems[J].Journal of Marketing Research,2000,37(3):363-375
[16] Herlocker J L.Evaluating Collaborative Filtering Recommender Systems[J].ACM Transactions on Information Systems,2004,22(1):5-53
[17] Xiang L.Practice of Recommendation system[M].Beijing:Posts & Telecom Press,2012(in Chinese) 项亮.推荐系统实践[M].北京:人民邮电出版社, 2012
[18] Deng A L,Zhu Y Y,Shi B L.A collaborative filter recommendation algorithm based on item rating prediction[J].Journal of Software,2003,4(9):1621-1628(in Chinese) 邓爱林,朱扬勇,施伯乐.基于项目评分预测的协同过滤推荐算法[J].软件学报,2003,14(9):1621-1628
[19] Luo Q,Miao X J,Wei Q.Further research on collaborative filtering algorithm for sparse data[J].Computer Science,2014,41(6):264-268(in Chinese) 罗琦,缪昕杰,魏倩.稀疏数据集协同过滤算法的进一步研究[J].计算机科学,2014,41(6):264-268
[20] Sun Z,Luo N,Kuang W.One real-time personalized recommendation systems based on Slope One algorithm[C]∥ Eighth International Conference on Fuzzy Systems and Knowledge Discovery( FSKD 2011).Shanghai,China.2011:1826-1830
[21] Liu Z K,Zhang C,Zhang Y C,et al.Solving the Cold-Start Problem in Recommender Systems with Social Tags[J].Epl,2010,2(2):28002-28007
[22] Luo X,Ouyang Y X,Xiong Z,et al.The effect of similarity support in K-nearest-neighborhood based collaborative filtering[J].Chinese Journal of Computers,2010,3(8):1437-1445 (in Chinese) 罗辛,欧阳元新,熊璋,等.通过相似度支持度优化基于K近邻的协同过滤算法[J].计算机学报,2010,33(8):1437-1445
[23] Wang Pu,Ye Hong-wu.A Personalized Recommendation Algorithm Combining Slope One Scheme and User Based Collaborative Filtering [C]∥ International Conference on Industrial and Information Systems.2009:152-154
[24] Shani G,Brafman R,Heckerman D.An MDP-based recommender system[J].Joural of Machine Learning Research,2005,6(1):1265-1295
[25] Esslimani I,Brun A,Boyer A.Densifying a Behavioral Recommender System by Social Network Link Prediction Methods[J].Social Network Analysis and Mining,2011,1(3):159-172
[26] Herlocker J L,Konstan J A,Terveen L G,et al.Evaluating Collaborative Filtering Recommender Systems[J].ACM Transations on Information Systems,2004,2(1):5-53
[27] Zhou Tao,KUSCSIK Z,Liu Jian-guo,et al.Solving the apparent diversity-accuracy dilemma of recommender systems[J].PNAS,2010,7(10):4511-4515
[28] Guo G,Zhang J,Yorke-Smith N.A novel Bayesian similarity measure for recommender systems[C]∥ International Joint Conference on Artificial Intelligence.2013:2619-2625
[29] Guo G,Zhang J,Thalmann D.A Simple But Effective Method to Incorporate Trusted Neighbors in Recommender Systems[C]∥International Conference on User Modeling,Adaptation and Personalization.2012:114-125

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