LJCSNS International Joumal of Computer Science and Network Security, VOL 6 No5A, May 2006 6T. Joachims, Text Categorization with Support Vector Machines: Learning with Many Relevant Features Tadachika Ozono received his bachelor Proceedings of the European Conference on Machine degree in engineering from Nagoya Institute Learning. 1998 of Technology, his master degree in [4]G. H. John, R Kohavi, K. Pfleger, Irrelevant Features and the gineering from Nagoya Institute of Subset Selection Problem, Proceedings of the eleventh nology, and his Ph D in International Conference on Machine Learning, pp. 121-129 from Nagoya Institute of Technology. He is a research associate of the Graduate School of 5 T. Kudo, T iny SVM: Support Vector Machines ttp: //cl-aist-nara ac ip/-taku-ku/software/TinySVM, 2001 Nagoya Institute of Technology. His research topic is a wel [6]D. Lewis and M. Ringuette, A comparison of two learning intelligence using multiagent and machine learning technologies. algorithms for text categorization, Third Annual Symposium on Document Analysis and Information Retrieval, pp 81-93 1994 [7 K Nigam, J. Lafferty and A Mc Callum, Using Maximum Entropy for Text Classification, IJCAl-99 Workshop on Machine Learning for Information Filtering, 1999 8 T Ozono, S. Goto, N Fujimaki, and T Shintani, P2P based Knowledge Source Discovery on Research Support System Papits, The First International Joint Conference on utonomous Agents Multiagent Systems(AAMAS 2002), 3J.R. Quinlan, Induction of decision trees, Machine Learni pp [10J M. Sahami, S Dumais, D. Heckerman and E. Horvitz, A Bayesian approach to filtering junk e-mail, AAAl/CML Workshop on Learning for Text Categorization, 1998 [11]P Soucy and G. w. Mineau, A Simple Feature Selection Method for Text Classification, Proceedings of International oint Conference on Artificial Intelligence(UCAlO1), pp 897-902,2001 [12Y Yang andX. Liu, A re-examination of text categorization methods, 22nd Annual International SIGIR, Pp 42-49, 1999 [13]Y. Yang and J. O. Perdersen, A Comparative Study on Feature Selection in Text Categorization, Proceedings of the Fourteenth International Confer on Machine Learning(ICML 97), 1997IJCSNS International Journal of Computer Science and Network Security, VOL.6 No.5A, May 2006 23 [3] T. Joachims, Text Categorization with Support Vector Machines: Learning with Many Relevant Features, Proceedings of the European Conference on Machine Learning, 1998. [4] G. H. John, R. Kohavi, K. Pfleger, Irrelevant Features and the Subset Selection Problem, Proceedings of the Eleventh International Conference on Machine Learning, pp.121-129, 1994. [5] T. Kudo, TinySVM: Support Vector Machines, http://cl-aist-nara.ac.jp/~taku-ku/software/TinySVM ,2001 [6] D. Lewis and M. Ringuette, A comparison of two learning algorithms for text categorization, Third Annual Symposium on Document Analysis and Information Retrieval, pp 81-93, 1994. [7] K. Nigam, J. Lafferty and A. McCallum, Using Maximum Entropy for Text Classification, IJCAI-99 Workshop on Machine Learning for Information Filtering, 1999. [8] T. Ozono, S. Goto, N. Fujimaki, and T. Shintani, P2P based Knowledge Source Discovery on Research Support System Papits, The First International Joint Conference on Autonomous Agents & Multiagent Systems(AAMAS 2002), 2002. [9] J. R. Quinlan, Induction of decision trees, Machine Learning, 1 (1) pp 81-106, 1986. [10] M. Sahami, S. Dumais, D. Heckerman and E. Horvitz, A Bayesian approach to filtering junk e-mail, AAAI/ICML Workshop on Learning for Text Categorization, 1998. [11] P. Soucy and G. W. Mineau, A Simple Feature Selection Method for Text Classification, Proceedings of International joint Conference on Artificial Intelligence(IJCAI'01), pp. 897-902, 2001. [12] Y. Yang and X. Liu, A re-examination of text categorization methods, 22nd Annual International SIGIR, pp.42-49, 1999. [13] Y. Yang and J. O. Perdersen, A Comparative Study on Feature Selection in Text Categorization., Proceedings of the Fourteenth International Conference on Machine Learning(ICML'97), 1997. Tadachika Ozono received his bachelor degree in engineering from Nagoya Institute of Technology, his master degree in engineering from Nagoya Institute of Technology, and his Ph.D in engineering from Nagoya Institute of Technology. He is a research associate of the Graduate School of Computer Science and Engineering at Nagoya Institute of Technology. His research topic is a web intelligence using multiagent and machine learning technologies