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

Trained SVMs based rules extraction method 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)
Miao Zhang ; Coll. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou ; De-xian Zhang

The automatic text classification method aims to assign text files to one or more predefined categories according to the text information contained by all kinds of text format files. SVM is recognized as one of the most effective text classification methods for its high accuracy, but its black-box feature causes that the description of each category can not be given and explained. In this paper, a new rule extraction method for text classification based on trained SVMs is proposed to solve the bottleneck of SVMs. The experiments show that the proposed approach can improve the validity of the extracted rules remarkably compared to C4.5 either in speed or accuracy.

Published in:

IT in Medicine and Education, 2008. ITME 2008. IEEE International Symposium on

Date of Conference:

12-14 Dec. 2008

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.