基于一跳信任模型的协同过滤推荐算法

doi:10.11959/j.issn.1000-436x.2015130

Abstract

Abstract:

A collaborative filtering recommendation algorithm based on the trust network of social brings two problems that the choice of complex paths between nodes and the weak transfering of trust.Toward to these two problems,a one-jump trust model based on items was put forward,the model calculated the trust between users and items,defined the consumer’s trust attribute vector of social and calculated the direct and indirect distance one-jump by items,and then calculated the trust between users.A collaborative filtering algorithm(OneJ-TCF) is degined based on the model,moreover analysed and reorganized the relation between trust and similarity.The experiments show that this algorithm improves the degree of accuracy(reducing about 0.02 MAE),and saves about 50% training time at the same time.

Key words: recommendation algorithm, one-jump trust model, trust distance, trus

Xing-mao WANG,Xing-ming ZHANG,Jiang-xing WU. Collaborative filtering recommendation algorithm based on one-jump trust model[J]. Journal on Communications, 2015, 36(6): 193-200.

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[1]	荣辉桂, 火生旭, 胡春华 . 基于用户相似度的协同过滤推荐算法[J]. 通信学报, 2014,35(2): 16-24. RONG H G , HUO S X , HU C H . User similarity-based collaborative filtering recommendation algorithm[J]. Journal on Communications, 2014,35(2): 16-24.
[2]	李英壮, 高拓, 李先毅 . 基于云计算的视频推荐系统的设计[J]. 通信学报, 2013,34(Z2): 138-140. LI Y Z , GAO T , LI X Y . Design of video recommender system based on cloud computing[J]. Journal on Communications, 2013,34(Z2): 138-140.
[3]	丁欣, 马严, 吴军 . 适用于校园网的视频推荐系统的设计与实现[J]. 通信学报, 2013,34(Z2): 175-179. DING X , MA Y , WU J . Design and implementation of a video recommendation system in campus network[J]. Journal on Communications, 2013,34(Z2): 175-179.
[4]	YOU W , YE S S . A survey of collaborative filtering algorithm applied in E-commerce recommender system[J]. Computer Technology and Development, 2006,16(9): 70-72.
[5]	GOLBECK J , HENDLER J . Inferring trust relationships in Web based social networks[J]. ACM Transactions on Internet Technology, 2006,6(4): 497-529.
[6]	POLO M , BOBBY B . Using trust in recommender system:an experimental analysis[A]. Proceedings of iTrust2004 International Conference[C]. 2004.
[7]	AVESANI P , MASSA P , TIELLA R . A trust-enhanced recommender system application:molesking[A]. Proceedings of the 2005 ACM Symposium on Applied Computing[C]. Santa, 2005. 1589-1593.
[8]	YUAN Q , ZHAO S W , LI C ,et al. Augmenting collaborative recommender by fusing explicit social relationships[A]. ACM Conference on Recommender System Workshop on Recommender Systems and the Social Web[C]. New York, 2009. 49-56.
[9]	JEBRIN A S , WILLIAMS M A . Credibility-aware web-based social network recommender:follow the leader[A]. Proceedings of the 2nd ACM RecSys’10 Workshop on Recommender System and the Social Web[C]. Barcelona, 2010.
[10]	MA H KIN ,e G I LYU M R , LI N .Learning to recommend with social trustnsemble[A]. Proceedings of the 32rid International ACM SIGIR Conference on Research and Development Information Retrieval[C]. New York,USA, 2009. 203-210.
[11]	田俊峰, 鲁玉臻, 李宁 . 基于推荐的信任链管理模型[J]. 通信学报, 2011,32(10): 1-9. TIAN J F , LU Y Z , LI N . Trust chain management model based on recommendation[J]. Journal on Communications, 2011,32(10): 1-9.
[12]	唐文, 陈钟 . 基于模糊集合理论的主观信任管理模型研究[J]. 软件学报, 2003,14(8): 1401-1408. TANG W , CHEN Z . Research of subjective trust management model based on the fuzzy set theory[J]. Journal on Software, 2003,14(8): 1401-1408.
[13]	王新洲, 史文中, 王树良 . 模糊空间信息处理[M]. 武汉：武汉大学出版社, 2003. WANG X Z , SHI W Z , WANG S L . Fuzzy Spatial Information Processing[M]. Wuhan: Wuhan University PressPress, 2003.
[14]	ZIEGLER C N , LAUSEN G . Analyzing correlation between trust and user similarity in online communities[A]. The Second International Conference on Trust Management[C]. Oxford, 2004. 251-265.
[15]	朱郁筱, 吕琳媛 . 推荐系统评价指标综述[J]. 电子科技大学学报, 2012,41(2): 163-175. ZHU Y X , LV L Y . Evaluation metrics for recommender systems[J]. Journal of University of Electronic Science and Technology of China, 2012,41(2): 163-175.

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