Home           Contact us           FAQs           
 
   Journal Page   |   Aims & Scope   |   Author Guideline   |   Editorial Board   |   Search
    Abstract
2014 (Vol. 7, Issue: 5)
Article Information:

A Dempster-Shafer Model for Feature Selection in Text Categorization

P. Umar Sathic Ali and C. Jothi Venkateswaran
Corresponding Author:  P. Umar Sathic Ali 

Key words:  Dempter-shafer theory, feature selection, text categorization, , , ,
Vol. 7 , (5): 981-985
Submitted Accepted Published
January 31, 2013 March 02, 2013 February 05, 2014
Abstract:

In this study, we propose a feature selection method based on evident theoretic model for text categorization. The proposed model is formally expressed within the Dempster-Shafer Theory of Evidence. We discuss the way the theory is used to retrieve highly informative and relevant features from the document collection. The formal retrieval function is inferred from the said model and compared our proposed model with many of the conventional feature selection methods. Experimental evaluation on standard benchmark dataset has shown the effectiveness of the proposed method.
Abstract PDF HTML
  Cite this Reference:
P. Umar Sathic Ali and C. Jothi Venkateswaran, 2014. A Dempster-Shafer Model for Feature Selection in Text Categorization.  Research Journal of Applied Sciences, Engineering and Technology, 7(5): 981-985.
    Advertise with us
 
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Current Information
   Sales & Services
   Contact Information
  Executive Managing Editor
  Email: admin@maxwellsci.com
  Publishing Editor
  Email: support@maxwellsci.com
  Account Manager
  Email: faisalm@maxwellsci.com
  Journal Editor
  Email: admin@maxwellsci.com
  Press Department
  Email: press@maxwellsci.com
Home  |  Contact us  |  About us  |  Privacy Policy
Copyright © 2009. MAXWELL Science Publication, a division of MAXWELLl Scientific Organization. All rights reserved