摘要: 随着社交网络的快速发展、社交网络用户规模的不断扩大,如何为用户推荐感兴趣的信息变得越发困难。传统的推荐方法利用用户兴趣的历史数据来预测用户未来感兴趣的项目,忽视了社交网络中的信任关系,导致推荐方法的推荐质量不高。针对上述问题,提出了基于社会信任潜在因子模型的推荐方法。该方法引入社会信任来度量社交网络中朋友之间的隐含信任关系,根据社会信任程度来选择用户信任的朋友,对用户信任的朋友与目标用户的共同兴趣进行潜在因子分析,构建基于社会信任的潜在因子模型,实现目标用户的前k个项目推荐。真实数据集上的对比实验结果表明,基于社会信任潜在因子模型的推荐方法在推荐质量上优于现有的推荐方法。
[1] Andersen R,Borgs C,Chayes J,et al.Trust-based recommendation systems:an axiomatic approach[C]∥Proceedings of the 17th international conference on World Wide Web.Beijing,China,2008:199-208HT6〗 [2] Bisgin H,Agarwal N,Xu X.Investigating homophily in onlinesocial networks[C]∥Proceedings of 2010IEEE/WIC/ACM International Conference on Web Intelligence.WI,2010:533-536 [3] Canny J.Collaborative filtering with privacy via factor analysis[C]∥Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.Tampere,Finland,2002:238-245 [4] Caverlee J,Liu L,Webb S.Socialtrust:tamper-resilient trust establishment in online communities[C]∥Proceedings of the 8th ACM/IEEE-CS Joint Conference on Digital Libraries.Pittsburgh PA,PA,USA,2008:104-114 [5] Deshpande M,Karypis G.Item-based top-N recommendation algorithms[J].ACM Transactions on Information Systems,2004,22(1):143-177 [6] Golbeck J.Computer Science-Weaving a Web of trust[J].Scien-ce,2008,321(5896):1640-1641 [7] Golbeck J.Computing And Applying Trust In Web-Based Social Networks[D].University of Maryland,USA,2005 [8] Jamali M,Ester M.A matrix factorization technique with trust propagation for recommendation in social networks[C]∥Proceedings of the Fourth ACM Conference on Recommender Systems.Barcelona,Spain,2010:135-142 [9] Jamali M,Ester M.TrustWalker:a random walk model for combining trust-based and item-based recommendation[C]∥Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.Paris,France,2009:397-406 [10] Karypis G.Evaluation of Item-Based Top-N RecommendationAlgorithms[C]∥Proceedings of the tenth international confe-rence on Information and knowledge management.Atlanta,Georgia,USA,2001:247-254 [11] Kuter U,Golbeck J.SUNNY:a new algorithm for trust inference in social networks using probabilistic confidence models[C]∥Proceedings of the 22nd national conference on Artificial intelligence.Columbia,Canada,2007:1377-1382 [12] Ma H,King I,Lyu M R.Learning to recommend with socialtrust ensemble[C]∥Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval.Boston,MA,USA,2009:203-210 [13] Massa P,Avesani P.Trust-aware recommender systems[C]∥Proceedings of the 2007ACM conference on Recommender systems.Minneapolis,MN,USA,2007:17-24 [14] McPherson M,Smith-Lovin L,Cook J M.Birds of a Feather:Homophily in Social Networks[J].Annual Review of Sociology,2001,27(1):415-444 [15] Moghaddam S,Jamali M,Ester M,et al.FeedbackTrust:usingfeedback effects in trust-based recommendation systems[C]∥Proceedings of the third ACM conference on Recommender systems.New York,New York,USA,2009:269-272 [16] Niu S,Guo J,Lan Y,et al.Top-k learning to rank:labeling,ranking and evaluation[C]∥Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval.Portland,Oregon,USA,2012:751-760 [17] Sarwar B,Karypis G,Konstan J,et al.Item-based collaborative filtering recommendation algorithms[C]∥Proceedings of the 10th International Conference on World Wide Web.Hong Kong,China,2001:285-295 [18] Sztompka P.Trust:A Sociological Theory[M].Cambridge:Cambridge Univ.Press,1999 [19] Xing X,Zhang W,Jia Z,et al.Learning to recommend top-kitems in online social networks[C]∥Proceedings of the 2012World Congress on Information and Communication Technologies.WICT 2012,India,2012:1171-1176 [20] 周涛.个性化推荐的十大挑战[J].计算机协会通讯,2012,8(7):48-61 |
No related articles found! |
|