Cite this paper
L. Wei, B. Wei and B. Wang, "Text Classification Using Support Vector Machine with Mixture of Kernel," Journal of Software Engineering and Applications
, Vol. 5 No. 12, 2012, pp. 55-58. doi: 10.4236/jsea.2012.512B012
 V. Vapnik, “The nature of statistic learning theory. Springer, New York, 1995.
 T. Joachims, “Text Categorization with Support Vector Machines Learning with Many Relevant Features,” In European Conference on Machine Learning ( ECML). Chemnitz, Germany: [s.n.], 1998, pp. 137-142.
 T. Gartner, P. A. Flach, “WBCSVM: Weighted Bayesian Classification based on support vector machine,” 18th Int. Conf. on Machine Learning. Willianstown, Carla E. Brodley, Andrea Po-horeckyj Danyluk, (eds.), 2001, pp. 207–209.
 ChengHua Li, JuCheng Yang, S. C. Park, “Text categorization algorithms using semantic ap-proaches, corpus-based thesaurus and WordNet,” Expert Syst. Appl. 39(1), pp. 765-772, 2012.
 A. Ch. Mic-chelli, M. Pontil, “Learning the kernel function via regu-larization,” Journal of Machine Learning Research, 6, 2005, pp. 1099-1125.
 G. R.G. Lanckrient, N. Cris-tianini, P. Bartlett, L. El Ghaoui, M.I. Jordan. Learning the kernel matrix with semidefinite programming. Jour-nal of Machine Learning Research, 5, 2004, pp. 27-72.
 F.R. Bach, G. R.G. Lanckrient, M.I. Jordan. Multiple kernel learning, conic duality and the SMO al-gorithm. Twenty First International Conference on Ma-chine Learning, 2004, pp. 41-48.
 L.W. Wei, J.P. Li, Z.Y. Chen. Credit Risk Evaluation Using Support Vector Machine with Mixture of Kernel, The 7th International Conference on Computational Science 2007, Lecture Notes in Computer Science 4488, 2007, pp. 431-438.
 Institute of Computing Technology, Chi-nese Lexical Analysis System: http://www.nlp.org.cn/project/project.php?proj_id=6.
 F. Jiang, “Research on Chinese Text Categorization based on Support Vector Machine,” Degree of Master paper, Chongqing University, 2009.