Research Article Open Access

Chi Square Feature Extraction Based Svms Arabic Language Text Categorization System

Abdelwadood Moh’d A MESLEH1
  • 1 , Afganistan
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

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).

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Keywords

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