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Research on Two Classes Text Categorization Method Based on an Improved Support Vector Machine |
Ying Wei1 Wang Zhengou1 An Jinlong2 |
1 (Institute of Systems Engineering, Tianjin University, Tianjin 300072, China)
2 (Hebei University of Technology, Tianjin 300130, China) |
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Abstract This paper puts forward a method of two text categorization classes based on the pre-extracting support vectors and fuzzy circulated iterative algorithm. Compared with the conventional Support Vector Machines(SVM), the present method possesses much higher computation efficiency. This paper gives the concrete procedure of the algorithm, and applies it to the text classification. Experimental results demonstrate the effectiveness and the efficiency of the approach.
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Received: 29 August 2005
Published: 25 December 2005
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Corresponding Authors:
Ying Wei
E-mail: nobertying@126.com
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About author:: Ying Wei,Wang Zhengou,An Jinlong |
1Talwar V, Mitra P. Web mining in soft computing framework: relevance, state of the art and future directions. Neural Networks, IEEE Transactions on , Volume: 13 , Issue: 5 , Sep 2002, 1163-1177
2Chih-Wei Hsu, Chih-Jen Lin. A comparison of methods for multiclass support vector machines. IEEE Transactions on Neural Networks, 2002, 13(2):415-425
3安金龙,王正欧. 一种新的支持向量机多类分类方法. 信息与控制,2004,(3):262-267
4史忠植. 知识发现. 北京 清华大学出版社,2002
5Wemter G, Arevian, and C pancjev. Recurrent Neural Network Learing for Text Routing. Proceedings of the International Conference on Artificial Neural Network. Edinburgh, UK,1999, 898-903
6Rennie and Ryan Rifkin. Improving Multiclass Text Classification with the Support Vector Machine\ [DB/OL\]. Online at: \ [www.ai.mit.edu/research/abstractabstracts2001/machine-learning\] Available: May 23,2002
7Joachims T. Text categorization with Support Vector Machines:Learning with Many Relevant Features. Proceedings10th European Conference on Machine Learning.1998, ECML-98, 137-142
8Susan Dumais, John Platt, David Hekerman, and M Sahami. Inductive Learning Algorithms and Representations for text Categorization. 7th International Conference on Information and Knowledge Management, 1998
9Bssu A , Watters C, Shepherd M. Support Vector Machines for Text categorization . System Sciences, proceedings of the 36th Annual Hawaii International, 6-9Jan, 2003, 7-13
10王明春,王正欧, 张楷等. 一种基于CHI值特征选取的粗糙集文本分类规则抽取方法. 计算机应用, 2005(5):1026-1028
11Vladimir N Vapnik. An overview of Statistical Learning Theory. IEEE Transactions on Neural Networks, 1999,10(5): 988-999
12Nello Cristianini & John Shawe-Taylor. An Introduction To Support Vector Machines.New York, USA, Cambridge University Press,2000
13Vasehgi S V. State duration modeling in hidden Markov models. Signal processing, 1995, (41):31-41
14Vladimir N, Vapnik. Statistical Learning Theory. Wiley-Interscience Publication, John Wiley&Sons,Inc.New York, USA,1998
15Mokhtar Bazaraa, Hanif Sherali, and Shetty. Nonlinear Programming: Theory and Algorithms,2nd Edition.Hamilton printing, John Wiley&Sons, Inc.New York, USA, 1993
16安金龙,王正欧. 一种适合于增量学习的支持向量机的快速循环算法. 计算机应用, 2003,23(10):12-14
17安金龙, 王正欧. 预抽取支持向量机的支持向量. 计算机工程, 2004, 30 (10): 10-12
18Zhang Li, Zhou Weida, Jiao Licheng. Pre-extracting Support Vectors fof Support Vector Machine. Signal Processing Proceedings, 2000 (3):1432-1435
19Cortes C, Vladimir N Vapnik. Support Vector Networks. Machine Learning, 1995 (20):273-297
20John Platt. Fast Training of Support Vector Machines using Sequential Minimal Optimization. Advances in Kernel Methods-Support Vector Learning. Cambridge, MA, MIT Press, 1999,185-208
21Christopher Burges. A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery, 1998, 2(2):121-167 |
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