Chi Square Feature Extraction Based Svms Arabic Language Text Categorization System
Abdelwadood Moh’d A MESLEH
DOI : 10.3844/jcssp.2007.430.435
Journal of Computer Science
Volume 3, Issue 6
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).
© 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.