NDLI: A New Chinese Text Feature Selection Method in Centroid-Based Classifier

Content Provider	IEEE Xplore Digital Library
Author	Yijun Gu Rong Wang Jianhua Wang Jiangde Yu
Copyright Year	2008
Description	Author affiliation: Coll. of Inf. Security & Eng., Chinese People's Public Security Univ., Beijing (Yijun Gu; Rong Wang)
Abstract	Feature selection method based on text study is a mainstream method currently, whose research key lies in finding out one suitable feature assessment method, which can reduce the numbers of the words to be processed as less as possible in the situation of not decreasing classification precision, to improve the speed and the efficiency of classification. A new feature assessment method entropy ratio is proposed in this paper on the base of researching the classical feature assessment methods in the existing literature. This method not only considered feature classification ability, but also the feature generalization ability. It is a new and better choice to apply the centroid-based classifier to improve the effect of classification. Experimental results show that the effect obtained by using this method to select features is obviously superior to the one obtained by other methods, especially when the feature selected is less.
Starting Page	88
Ending Page	92
File Size	293521
Page Count	5
File Format	PDF
ISBN	9780769531519
DOI	10.1109/ISIP.2008.108
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-23
Publisher Place	Russia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Standardization Educational institutions Support vector machines Automatic text classification Bayesian methods Text categorization Support vector machine classification Information security Text Feature Selection Information processing Frequency Centroid-Based Classifier Classification tree analysis
Content Type	Text
Resource Type	Article

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