A Multilayer Method of Text Feature Extraction Based on CILIN

Author

Li, Xin-fu ; Zhao, Lei-lei

Author_Institution

Fac. of Math. & Comput., Hebei Univ., Baoding

fYear

2008

fDate

Aug. 29 2008-Sept. 2 2008

Firstpage

48

Lastpage

52

Abstract

The feature extraction is the most critical technology of text categorization. The method of feature extraction from Chinese text based on CILIN is different from the conventional feature extraction, which uses two feature extraction methods. This method is good at dealing with synonyms and polysemes, and reducing the dimension. Firstly, it uses the method of feature extraction from Chinese text based on CILIN to analyze the meaning of key words. Secondly, use the mutual information to extract the feature, it can give the relation between class and lemma. The experiment results proposed that comprehend to the meaning of key words can distinctively improve the text classification precision.

Keywords

feature extraction; text analysis; CILIN; Chinese text; multilayer method; text categorization; text classification precision; text feature extraction; Feature extraction; Frequency; Mathematics; Mutual information; Niobium; Nonhomogeneous media; Statistics; Support vector machine classification; Support vector machines; Text categorization; CILIN; feature extraction; text categorization;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Information Technology, 2008. ICCSIT '08. International Conference on

Conference_Location

Singapore

Print_ISBN

978-0-7695-3308-7

Type

conf

DOI

10.1109/ICCSIT.2008.57

Filename

4624831