入门-资料参考
仅作学习使用
先看一些资料。
推荐算法综述，https://blog.csdn.net/a378812/article/details/83033713
参考文献：
[1] Su X, Khoshgoftaar T M. Asurvey of collaborative filtering techniques[M]. Hindawi Publishing Corp. 2009.
[2] J. Bobadilla, F. Ortega, A.Hernando, A. Gutiérrez, Recommender systems survey, Knowledge-Based Systems, 46(2013) 109-132.
[3] P. Resnick, H.R. Varian, Recommender systems, Communications of theACM, 40 (1997) 56-58.
[4] M. Pazzani, D. Billsus, Content-based recommendation systems, in: P.Brusilovsky, A. Kobsa, W. Nejdl (Eds.) The Adaptive Web, Springer BerlinHeidelberg2007, pp. 325-341.
[5] Salton G. Automatic text processing[M]. Addison-Wesley LongmanPublishing Co. Inc. 1989.
[6] Deerwester S. Indexing by latent semantic analysis[J]. Journal ofthe Association for Information Science & Technology, 1990, 41(6):391-407.
[7] Hofmann T. Unsupervised Learning by Probabilistic Latent SemanticAnalysis[J]. Machine Learning, 2001, 42(1-2):177-196.
[8] M. Deshpande, G. Karypis, Item-based top-N recommendationalgorithms, ACM Transactions on Information Systems (TOIS), 22 (2004) 143-177
[9] P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, J. Riedl,GroupLens: an open architecture for collaborative filtering of netnews, Proceedings of the 1994 ACM Conference onComputer Supported Cooperative Work, ACM, Chapel Hill, North Carolina, USA,1994, pp. 175-186.
[10] Lu J, Wu D, Mao M, et al.Recommender system application developments[J]. Decision Support Systems, 2015,74(C):12-32.
[11] M. Nilashi, O.b. Ibrahim, N.Ithnin, Multi-criteria collaborative filtering with high accuracy using higherorder singular value decomposition and Neuro-Fuzzy system, Knowledge-BasedSystems, 60 (2014) 82-101.
[12] G.-R. Xue, C. Lin, Q. Yang, W.Xi, H.-J. Zeng, Y. Yu, Z. Chen, Scalable collaborative filtering usingcluster-based smoothing, Proceedings ofthe 28th Annual International ACM SIGIR Conference on Research and Developmentin Information Retrieval, ACM, Salvador, Brazil, 2005, pp. 114-121.
[13] S.K. Shinde, U. Kulkarni,Hybrid personalized recommender system using centering-bunching basedclustering algorithm, Expert Systems with Applications, 39 (2012) 1381-1387.
[14] M.A. Ghazanfar, A.Prügel-Bennett, Leveraging clustering approaches to solve the gray-sheep usersproblem in recommender systems, Expert Systems with Applications, 41 (2014)3261-3275.
[15] G.Shani,D.Heckerman,and R.I.Brafman,“AnMDP-based recommender system,” Journal of Machine Learning Research, vol. 6,pp. 1265–1295, 2005.
[16] R. A. Howard, DynamicProgramming and Markov Processes, MIT Press, Cambridge, Mass, USA, 1960.
[17] R. S. Sutton and A. G. Barto,Reinforcement Learning: An Introduction, MIT Press, Cambridge, Mass, USA, 1998.
[18] Felfernig A, Burke R.Constraint-based recommender systems: technologies and research issues[M].2008.
[19] Tsang E P K. Foundations ofconstraint satisfaction[M]. DBLP, 1993.
[20] B. Smyth, Case-basedrecommendation, in: P. Brusilovsky, A. Kobsa, W. Nejdl (Eds.) The Adaptive Web,Springer Berlin Heidelberg2007, pp. 342-376.
[21] Burke, R., Hammond, K., andYoung, B. 1997. The FindMe Approach to Assisted Browsing. IEEE Expert, 12(4),pages 32-40.
[22] Huang Z, Zeng D D, Chen H.Analyzing Consumer-Product Graphs: Empirical Findings and Applications inRecommender Systems[J]. Management Science, 2007, 53(7):1146-1164.
[23] Zhou T, Ren J, Medo M, et al.Bipartite network projection and personal recommendation.[J]. Physical Review EStatistical Nonlinear & Soft Matter Physics, 2007, 76(2):046115.
[24] Zhang S, Yao L, Sun A. DeepLearning based Recommender System: A Survey and New Perspectives[J]. 2017.
[25] Paul Covington,Jay Adams,and EmreSargin .2016. Deep neural networks for youtube recommendations.In Proceedingsof the 10th ACM Conference on Recommender Systems.ACM,191–198.
[26] Cheng H T, Koc L, Harmsen J, etal. Wide & Deep Learning for Recommender Systems[J]. 2016:7-10.
[27] 孟婷婷. 基于社交网络的推荐算法应用研究[D]. 重庆大学, 2015.
