Cart (Loading....) | Create Account
Close category search window
 

A new feature selection method based on distributional information for Text Classification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Nianyun Shi ; Coll. of Comput. & Commun. Eng., China Univ. of Pet. (East China), Dongying, China ; Lingling Liu

Feature Selection (FS) is one of the most important issues in Text Classification (TC). A good feature selection can improve the efficiency and accuracy of a text classifier. Based on the analysis of the feature's distributional information, this paper presents a feature selection method named DIFS. In DIFS a new estimation mechanism is proposed to measure the relevance between feature's distribution characteristics and contribution to categorization. In addition, two kinds of algorithms are designed to implement DIFS. Experiments are carried out on a Chinese corpus and by comparison the proposed approach shows a better performance.

Published in:

Progress in Informatics and Computing (PIC), 2010 IEEE International Conference on  (Volume:1 )

Date of Conference:

10-12 Dec. 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.