计算机科学 ›› 2015, Vol. 42 ›› Issue (9): 230-234.doi: 10.11896/j.issn.1002-137X.2015.09.044
郑炅,石 刚
ZHENG Jiong and SHI Gang
摘要: 在电子商务中,用户对商品的决策很大程度上取决于用户间的社会信任关系。传统的推荐算法往往考虑用户间的静态关系,即决策依赖的社会关系图是不变的。实际上,用户对好友的信任度往往随着时间的变化而变化。为了描述动态的信任关系在推荐系统中的作用,提出了一种基于动态信任关系的推荐算法。首先,提出了一种考虑用户的静态兴趣和静态信任关系的产生式模型;然后,分别将时序因素加入到用户兴趣和信任关系的描述,并提出了相应的动态产生式模型。实验表明,提出的算法能很好地描述用户之间信任关系随时间的变化,并且与其它相关算法相比,评价值的预测准确性得到了明显的提高。
[1] 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):350-362 Xu Hai-ling,Wu Xiao,Li Xiao-dong,et al.Comparison study of Internet recommendation system [J].Journal of Software,2009,20(2):350-362 [2] Esparza G S,O’Mahony M P,Smyth B.Mining the real-time web:a novel approach to product recommendation[J].Knowledge-Based Systems,2012,29(3):3-11 [3] Pham M C,Cao Y,Klamma R,et al.A Clustering Approach for Collaborative Filtering Recommendation Using Social Network Analysis[J].J.UCS,2011,17(4):583-604 [4] Lops P,de Gemmis M,Semeraro G.Content-based recommender systems:State of the art and trends[M]∥Recommender Systems Handbook.Springer US,2011:73-105 [5] Koren Y,Bell R.Advances in collaborative filtering[M]∥Recommender Systems Handbook.Springer US,2011:145-186 [6] 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 Luo Xin,Ouyang Yuan-xin,Xiong Zhang,et al.The Effect of Similarity Support in k-Nearest-Neighborhood Based Collaborative Filtering[J].Chinese Journal of Computers,2010,33(8):1437-1445 [7] Breese J S,Heckerman D,Kadie C.Empirical analysis of predictive algorithms for collaborative filtering[C]∥Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence.1998:43-52 [8] Porteous I,Bart E,Welling M.Multi-HDP:A Non Parametric Bayesian Model for Tensor Factorization[C]∥AAAI.2008:1487-1490 [9] Blei D M,Ng A Y,Jordan M I.Latent dirichlet allocation[J].The Journal of Machine Learning Research,2003(3):993-1022 [10] Mackey L W,Weiss D,Jordan M I.Mixed membership matrix factorization[C]∥Proceedings of the 27th International Conference on Machine Learning(ICML-10).2010:711-718 [11] Koren Y.Collaborative filtering with temporal dynamics[J].Communications of the ACM,2010,53(4):89-97 [12] Xiong L,Chen X,Huang T K,et al.Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization[C]∥SDM.2010:211-222 [13] Xiang L,Yuan Q,Zhao S,et al.Temporal recommendation ongraphs via long-and short-term preference fusion[C]∥Procee-dings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.ACM,2010:723-732 [14] Rendle S,Freudenthaler C,Schmidt-Thieme L.Factorizing personalized markov chains for next-basket recommendation[C]∥Proceedings of the 19th International Conference on World Wide Web.ACM,2010:811-820 [15] Ma H,Yang H,Lyu M R,et al.Sorec:social recommendationusing probabilistic matrix factorization[C]∥Proceedings of the 17th ACM Conference on Information and Knowledge Management.ACM,2008:931-940 [16] Yuan Q,Chen L,Zhao S.Factorization vs.regularization:fusing heterogeneous social relationships in top-n recommendation[C]∥Proceedings of the fifth ACM Conference on Recommender Systems.ACM,2011:245-252 [17] Ma H,Zhou D,Liu C,et al.Recommender systems with social regularization[C]∥Proceedings of the fourth ACM InternationalConference on Web Search and Data Mining.ACM,2011:287-296 [18] Jamali M,Ester M.A transitivity aware matrix factorizationmodel for recommendation in social networks[C]∥Proceedings of the Twenty-Second international joint conference on Artificial Intelligence.2011:2644-2649 [19] Shen Y,Jin R.Learning personal+social latent factor model for social recommendation[C]∥Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.ACM,2012:1303-1311 [20] Ye M,Liu X,Lee W C.Exploring social influence for recommendation:a generative model approach[C]∥Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval.ACM,2012:671-680 [21] Salakhutdinov R,Mnih A.Probabilistic Matrix Factorization.http://www.cs.torontv.edu/~amnih/papers/pmf.pdf [22] 王越,程昌正.协同过滤算法在电影推荐中的应用[J].四川兵工学报,2014,35(5):86-88 Wang Yue,Cheng Chang-zheng.Application of Collaborative Filtering Algorithms in Movie Recommendation[J].Journal of Sichuan Ordnance,2014,5(5):86-88 |
No related articles found! |
|