Chi Square Feature Extraction Based Svms Arabic Language Text Categorization System
Abdelwadood Moh’d A MESLEH
Journal of Computer Science, Volume 3, Issue 6, pp. 430–435 · 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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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
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