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New Technology of Library and Information Service  2004, Vol. 20 Issue (7): 27-29    DOI: 10.11925/infotech.1003-3513.2004.07.06
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Study on Automatic Text Categorization with Support Vector Machine
Shi Jiebin
(Zhejiang University Library, Hangzhou 310029, China)
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Abstract  

A new machine learning method of Support Vector Machine (SVM), is applied in automatic text categorization. Comparing with the result achieved by k-nearest neighbor algorithm, the accuracy achieved by support vector machine is better; The effect of feature selection methods is smaller to SVM than the KNN method. The SVM is a potential and competitive method for automatic text categorization. The feature selection methods also affectes the accuracy of text categorization.
Key words： Automatic text categorization      Support vector machine      K-nearest neighbor algorithm      Feature selection     
Received: 23 February 2004      Published: 25 July 2004
: 

G254.361

 		 
Corresponding Authors: Shi Jiebin     E-mail: jbshi@lib.zju.edu.cn
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Cite this article:

Shi Jiebin. Study on Automatic Text Categorization with Support Vector Machine. New Technology of Library and Information Service, 2004, 20(7): 27-29.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2004.07.06     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2004/V20/I7/27

1史忠植.知识发现.北京：清华大学出版社，2002：334-363
2王梦云等.基于字频向量的中文文本自动分类系统.情报学报，2000，19（6）：644-649
3李勇等.网络文本数据分类技术与实现算法.情报学报，2002，21（1）：21-26
4庞剑锋等.基于向量空间模型的文本自动分类系统的研究与实现.计算机应用研究，2001（9）：23-26
5柳回春等.支持向量机的研究现状.中国图象图形学报，2002，7A（6）：618-623
6萧嵘等.支持向量机理论综述.计算机科学，2000，27（3）：1-3
7Vapnik, V., Statistical Learning Theory, New York, NY: Wiley, 1998
8陆玉昌等.向量空间法中单词权重函数的分析和构造.计算机研究与发展，2002，39（10）：1205-1210
9李凡等.关于文本特征抽取新方法的研究.清华大学学报（自然科学版），2001，41（7）：98-101
10朱明等.Web网页设别中的特征选择问题研究.计算机工程，2000，26（8）：35-37
11李蓉等.SVM-KNN分类器——一种提高SVM分类精度的新方法，电子学报，2002，30（5）：745-748
12Chang, C. et al, The analysis of decomposition methods for support vector machines, IEEE Transactions on Neural Networks,2000, 11 (4): 1003-1008
13孙健等.基于K-最近距离的自动文本分类研究.北京邮电大学学报，2001，24（1）：42-46
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