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ISSN: 1552-6607 (Online)
Research Article Open Access

Chi Square Feature Extraction Based Svms Arabic Language Text Categorization System

Abdelwadood Moh’d A MESLEH

Abstract

This paper aims to implement a Support Vector Machines (SVMs) based text classification system for Arabic language articles. This classifier uses CHI square method as a feature selection method in the pre-processing step of the Text Classification system design procedure. Comparing to other classification methods, our system shows a high classification effectiveness for Arabic data set in term of F-measure (F=88.11).

Journal of Computer Science
Volume 3 No. 6, 2007, 430-435

DOI: https://doi.org/10.3844/jcssp.2007.430.435

Submitted On: 3 April 2007 Published On: 30 June 2007

How to Cite: MESLEH, A. M. A. (2007). Chi Square Feature Extraction Based Svms Arabic Language Text Categorization System . Journal of Computer Science, 3(6), 430-435. https://doi.org/10.3844/jcssp.2007.430.435

Open AccessCopyright: © 2007 Abdelwadood Moh’d A MESLEH. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • Arabic Text Classification
  • Arabic Text Categorization
  • CHI Square feature extraction