Computer Science ›› 2017, Vol. 44 ›› Issue (4): 288-294.doi: 10.11896/j.issn.1002-137X.2017.04.059
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ZENG An and XU Xiao-qiang
[1] TAKCS G,PILSZY I,NEMETH B,et al.Investigation of various matrix factorization methods for large recommender systems[C]∥IEEE International Conference on Data Mining Workshops,2008(ICDMW’08).IEEE,2008. [2] MNIH A,SALAKUTDINOV R.Probabilistic matrix factorization[C]∥Advances in Neural Information Processing Systems.2007:1257-1264. [3] LI P P,XIAO R L,DENG X G,et al.A Novel Appocach to Matrix Factorization Recommender System Using Gravitational Impacts[J].Journal of Chinese Computer Systems,2015,6(4):696-700.(in Chinese) 李鹏澎,肖如良,邓新国,等.一种融合引力影响的新的矩阵分解推荐方法[J].小型微型计算机系统,2015,36(4):696-700. [4] TU D D,SHU C C,YU H Y.Using Unified Probabilistic Matrix Factorization for Contextual Advertisement Recommendation[J].Journal of Software,2013,4(3):454-464.(in Chinese) 涂丹丹,舒承椿,余海燕.基于联合概率矩阵分解的上下文广告推荐算法[J].软件学报,2013,24(3):454-464. [5] WANG D,CHEN Z,YUE W J,et al.Probabilistic matrix factorization recommendation with explicit and implicit feedback[J].Journal of Computer Applications,2015,35(9):2574-2578.(in Chinese) 王东,陈志,岳文静,等.基于显式与隐式反馈信息的概率矩阵分解推荐[J].计算机应用,2015,35(9):2574-2578. [6] JAMALI M,ESTER M.A matrix factorization technique with trust propagation for recommendation in social network[C]∥Proc of the ACM Recommender Systems Conf.New York:ACM Press,2010. [7] MASSA P,AVESANI P.Trust-aware collaborative filtering for recommender systems[J].Lecture Notes in Computer Science,2004,3290:492-508. [8] VINCENT S Z,BOI F.Using hierarchical clustering for learning the ontologies used in recommendation systems[C]∥Procee-dings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.San Jose,California,United States,2007. [9] ZOU B Y,LI C P,TAN L W,et al.Social Recommendations Based on User Trust and Tensor Factorization[J].Journal of Software,2014,5(12):2852-2864.(in Chinese) 邹本友,李翠平,谭力文,等.基于用户信任和张量分解的社会网络推荐[J].软件学报,2014,5(12):2852-2864. [10] TANG J L,GAO H J,HU X,et al.Context-Aware ReviewHelpfulness Rating Prediction[C]∥RecSys’13.2013. [11] PENG L,ZHOU Q H,QIU J T.Research on the Model of Helpfulness Factors of Online Customer Reviews[J].Computer Science 2011,38(8):205-207.(in Chinese) 彭岚,周启海,邱江涛.消费者在线评论有用性影响因素模型研究[J].计算机科学,2011,38(8):205-207. [12] MCAULEY J,FRIEDKIN J.Hidden factors and hidden topics:understanding rating dimensions with review text[C]∥RecSys.2013. [13] MENG X W,LIU S D,ZHANG Y J,et al.Research on SocialRecommender Systems[J].Journal of Software,2015,6(6):1356-1372.(in Chinese) 孟祥武,刘树栋,张玉洁,等.社会化推荐系统研究[J].软件学报,2015,6(6):1356-1372. [14] MA H,YANG H X, LYU M R,et al.Sorec:Social recommendation using probabilistic matrix factorization[C]∥CIKM.2008. [15] MA H,ZHOU D,LIU C,et al.Recommender systems with social regularization[C]∥WSDM.2011. [16] TANG J L,HU X,GAO H J,et al.Exploiting local and global social context for recommendation[C]∥IJCAI.2013. [17] YANG B,HUI F,JIE Z.Topicmf:Simultaneously exploitingratings and reviews for recommendation[C]∥AAAI.2014 [18] WANG S H,TANG J L,LIU H.Toward Dual Roles of Users in Recommender Systems[C]∥CIKM.2015. [19] MCPHERSON M,SMITH-LOVIN L,COOK J M.Birds of afeather:Homophily in social networks[J].Annual Review of Sociology,2001,27(1):415-444. [20] YU L,LIU L,LUO Z H.Comparison and Analysis o n E-Commence Recommenda tion Method in China[J].System Enginee-ring Theory and Practice,2004,24(8):96-101.(in Chinese) 余力,刘鲁,罗掌华.我国电子商务推荐策略的比较分析[J].系统工程理论与实践,2004,24(8):96-101. |
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