DocumentCode :
2839080
Title :
A improved feature weighting algorithm for Chinese text classification
Author :
Hui, Dong ; Siqing, Yin
Author_Institution :
Sch. of Electron. & Comput. Sci. & Technol., North Univ. of China, Taiyuan, China
Volume :
6
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
Based on analyzing traditional feature weighting algorithm and according to the problem that the traditional feature weighting algorithm only considers term frequency and inverse document frequency, a improved weighting algorithm is put forward, that is, synthesizing the length, position and class information of term when computing its weight. Then verify effectiveness of the classification by KNN classifier. Experimental results show that this algorithm can improve the classification accuracy and achieve great results of classification.
Keywords :
feature extraction; pattern classification; text analysis; Chinese text classification; KNN classifier; feature weighting algorithm; inverse document frequency; Education; Feature; Feature weighting; KNN classification algorithm; Text Classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5620717
Filename :
5620717
Link To Document :
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