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Improved rating prediction model basing on trust network and random walk strategy


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Improved rating prediction model basing on trust network and random walk strategy
Xiao Zhiyu1Zhai Yuqing12
1.School of Computer Science and Engineering;
2.Key Lab of Computer Network & Information Integration,Southeast University,Nanjing 211189,China
recommender trust network random walk rating prediction TrustWalker user similarity TopN rating referential users
In order to improve the accuracy of the rating prediction in recommender systems,the ReferentialUserWalker model based on TrustWalker is proposed here.The model is combined with the random walk strategy on the trust network and the item-based recommendation to improve the accuracy of rating prediction and to find the TopN trusted rating referential users associated with the trust weight to predict the rating.And then effect of noise data is reduced.The experiment results prove that the model in this paper has higher accuracy of rating prediction than TrustWalker.


[1] Zan Huang,Zeng Daniel,Chen Hsinchun.A comparison of collaborative-filtering recommendation algorithms for e-commerce[J].IEEE Intelligent Systems,2007,22(5):68-78.
[3]Massa P,Bhattacharjee B.Using trust in recommender systems:An experimental analysis[M].Berlin,Germany:Springer,2004.
[4]Golbeck J.Computing and applying trust in Web-based social networks[D].Washton D C,US:University of Maryland College Park,2005.
[5]Jamali M,Ester M.TrustWalker:A random walk model for combining trust-based and item-based recomm-endation[A].Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining[C].Pairs,France:ACM,2009:397-406.
[6]Sarwar B,Karypis G,Konstan J,et al.Item-based collaborative filtering recommendation algorithms[A].Proceedings of the 10th International Conference on World Wide Web[C].Hong Kong,China:ACM,2001:285-295.
[7]Jannach D,Zanker M,Felfernig A,et al.Recommender systems:An introduction[M].New York,US:Cambridge University Press,2010.
[8]Watts D J.Six degrees:The science of a connected age[M].New York,US:WW Norton & Company,2004.
[9]Jamali S M.Probabilistic models for recommendation in social networks[D].Burnaby,Canada:School of Computing Science,Simon Fraser University,2013.
[10]Massa P.Epinions datasets[EB/OL].http://www.trustlet.org/wiki/Epinions_dataset,2011-11-04.

[11]Massa P,Avesani P.Trust-aware recommender systems[A].Proceedings of the 2007 ACM Conference on Recommender Systems[C].Minneapolis,US:ACM,2007:17-24.

Zhang Fuguo.Survey of online social network based personalized recommendation[J].Journal of Chinese Computer Systems,2014,35(7):1470-1476.
Tan Xueqing,Huang Cuicui,Luo Lin.A review of research on trust recommendation in social networks[J].New Technology of Library and Information Service,2014,30(11):10-16.


Last Update: 2015-10-31