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《Journal of Hangzhou Dianzi University》 2010-06
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A Method of Chinese Question Classification Based on RST and SVM

DONG Yun-yao,CHEN Xiao-cui,HUANG Wei(School of Computer,Hangzhou Dianzi University,Hangzhou Zhejiang 310018,China)  
Aimed at the shortcomings of support vector machine(SVM) classification such as large amount of data quantity dimension,slowly processing and so on,a new method CRV was suggested,it uses attribute reduction in rough set theory to preprocess primitive great sample data,improve the convergence speed and accuracy of classification of SVM in eliminate redundant feature vector and reduce the dimension of sampled data space.Through the application of this method was applied in classification for these questions in QA system based on the course of computer networks,and effectively enhance the question classification accuracy,verify the feasibility of this method.
【CateGory Index】: TP391.1
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