1、Department of AutomationXiamen UniversityYouchun Ji, Wenxing Hong*, Jianwei QiNovember, 2015 Missing Value Prediction Using Co-clustering and RBF for Collaborative FilteringDepartment of Environmental Science 8-Jun-2006 1Department of Environmental Science 8-Jun-2006CWebsiteI 17du.infoJob recommenda
2、tionExpert finding News recommendation2012-2014 2014-now 2014-now2Department of Environmental Science 8-Jun-2006OutlineIntroduction1Algorithms & Experiments23Conclusion4The Problem Definition3Department of Environmental Science 8-Jun-2006Introduction1.Jannach, D., M. Zanker, A. Felfernig, &G. Friedr
3、ich, Recommender systems: an introduction. 2010: Cambridge University Press.2.Zheng, L., L. Li, W. Hong, &T. Li, PENETRATE: Personalized news recommendation using ensemble hierarchical clustering. Expert Systems with Applications, 2013. 40(6): p. 2127-2136.3.Das, A.S., M. Datar, A. Garg, &S. Rajaram
4、. Google news personalization: scalable online collaborative filtering. in Proceedings of the 16th international conference on World Wide Web. 2007. ACM.4.Breese, J.S., D. Heckerman, &C. Kadie. Empirical analysis of predictive algorithms for collaborative filtering. in Proceedings of the Fourteenth
5、conference on Uncertainty in artificial intelligence. 1998. Morgan Kaufmann Publishers Inc.Help users find interesting articles that match the users preference as much as possible.4Department of Environmental Science 8-Jun-2006IntroductionCollaborative filtering is one of the most successful methods
6、 for news recommendation systems. 1.Pazzani, M.J., A framework for collaborative, content-based and demographic filtering. Artificial Intelligence Review, 1999. 13(5-6): p. 393-408.2.Huang, Z., H. Chen, &D. Zeng, Applying associative retrieval techniques to alleviate the sparsity problem in collabor
7、ative filtering. ACM Transactions on Information Systems (TOIS), 2004. 22(1): p. 116-142.3.Hofmann, T., Latent semantic models for collaborative filtering. ACM Transactions on Information Systems (TOIS), 2004. 22(1): p. 89-115.4.Blei, D.M., A.Y. Ng, &M.I. Jordan, Latent dirichlet allocation. The Jou
8、rnal of machine Learning research, 2003. 3: p. 993-1022.5Department of Environmental Science 8-Jun-2006Motivation1.Zhang, S., W. Wang, J. Ford, &F. Makedon. Learning from Incomplete Ratings Using Non-negative Matrix Factorization. in SDM. 2006. SIAM.2.Dhillon, I.S. Co-clustering documents and words
9、using bipartite spectral graph partitioning. in Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining. 2001. ACM.The sparsity of user-item rating matrix will lead to the negative effect of collaborative filtering algorithm.Scenario 2Scenario 3Scenario
10、1In order to overcome the problem, we predict the values of user-item rating matrix combining two approaches: co-clustering and Radial Basis Function network (RBF).The number of news which users have read is far less than the news published on the website.6Department of Environmental Science 8-Jun-2
11、006OutlineIntroduction1Algorithms & Experiments23Conclusion4The Problem Definition7Department of Environmental Science 8-Jun-2006The Problem Definition1.George, T., &S. Merugu. A scalable collaborative filtering framework based on co-clustering. in Data Mining, Fifth IEEE International Conference on. 2005. IEEE.8Department of Environmental Science 8-Jun-2006OutlineIntroduction1Algorithms & Experiments23Conclusion4The Problem Definition9
