[1] FUNK S. Netflix update:try this at home[EB/OL]. (2011)[2017-01-20]. http://sifter.org/~simon/journal/20061211.html.
[2] SALAKHUTDINOV R, MNIH A. Probabilistic matrix factorization[J]. Advances in Neural Information Processing Systems, 2007:1257-1264.
[3] LEE D D, SEUNG H S. Algorithms for non-negative matrix factorization[J]. Proceedings of Advances in Neural and Information Processing Systems, 2000, 32(6):556-562.
[4] YANG B, LEI Y, LIU D, et al. Social collaborative filtering by trust[C]//Proceedings of the 23rd International Joint Conference on Artificial Intelligence.[S.l.]:AAAI Press, 2013:2747-2753.
[5] 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, Recsys 2010, Barcelona, Spain:[s.n.], 2010:135-142.
[6] 刘英南, 谢瑾奎, 张家利, 等. 社交网络中基于信任的推荐算法[J]. 小型微型计算机系统, 2015, 36(6):1165-1170. LIU Y N, XIE J K, ZHANG J L, et al. Recommendation algorithm based on trust in social network[J]. Journal of Chinese Computer Systems, 2015, 36(6):1165-1170.
[7] 肖晓丽, 钱娅丽, 李旦江, 等. 基于用户兴趣和社交信任的聚类推荐算法[J]. 计算机应用, 2016, 36(5):1273-1278. XIAO X L, QIAN Y L, LI D J, et al. Clustering recommendation algorithm based on user interest and social trust[J]. Journal of Computer Applications, 2016, 36(5):1273-1278.
[8] 杜永萍, 黄亮, 何明. 融合信任计算的协同过滤推荐方法[J]. 模式识别与人工智能, 2014, 27(5):417-425. DU Y P, HUANG L, HE M. Collaborative filteration recommendation algorithm based on trust computation[J]. Pattern Recognition and Artificial Intelligence, 2014, 27(5):417-425.
[9] GUO G B. Integrating trust and similarity to ameliorate the data sparsity and cold start for recommender systems[C]//Proceedings of the 7th ACM Conference on Recommender Systems. Hong Kong:ACM, 2013:451-454.
[10] GUO G B, ZHANG J, THALMANN D, et al. From ratings to trust:an empirical study of implicit trust in recommender systems[C]//Proceedings of the 29th Annual ACM Symposium on Applied Computing. Gyeongju, Korea:ACM, 2014:248-253.
[11] O'DONOVAN J, SMYTH B. Trust in recommender systems[C]//Proceedings of the 2005 International Conference on Intelligent User Interfaces. San Diego, California, USA:ACM, 2005.
[12] KOREN Y. Factorization meets the neighborhood:a multifaceted collaborative filtering model[C]//Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Las Vegas, USA:ACM, 2008:426-434.
[13] GUO G, ZHANG J, YORKE-SMITH N. TrustSVD:collaborative filtering with both the explicit and implicit influence of user trust and of item ratings[C]//Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence.[S.l.]:AAAI Press, 2015:123-129.
[14] 郭艳红, 邓贵仕, 雒春雨. 基于信任因子的协同过滤推荐算法[J]. 计算机工程, 2008, 34(20):1-3. GUO Y H, DENG G S, LUO C Y. Collaborative filtering recommendation algorithm based on factor of Trust[J]. Computer Engineering, 2008, 34(20):1-3.
[15] PAPAGELIS M, PLEXOUSAKIS D, KUTSURAS T. Alleviating the sparsity problem of collaborative filtering using trust inferences[C]//Trust Management, Third International Conference, iTrust 2005. Paris, France:Springer, 2005:224-239.
[16] SOTOS A, VANHOOF S, VAN DEN NOORTGATE W, et al. The transitivity misconception of pearson's correlation coefficient[J]. Statistics Education Research Journal, 2009, 8(2):33-55.
[17] GUO G B, ZHANG J, YORKE-SMITH N. A novel Bayesian similarity measure for recommender systems[C]//Proceedings of the 23rd International Joint Conference on Artificial Intelligence. Beijing, China:AAAI, 2013:2619-2625. |