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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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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 wordsAutomatic text categorization      Support vector machine      K-nearest neighbor algorithm      Feature selection     
Received: 23 February 2004      Published: 25 July 2004


Corresponding Authors: Shi Jiebin     E-mail:
About author:: Shi Jiebin

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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7Vapnik, V., Statistical Learning Theory, New York, NY: Wiley, 1998
12Chang, C. et al, The analysis of decomposition methods for support vector machines, IEEE Transactions on Neural Networks,2000, 11 (4): 1003-1008

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