CHI SQUARE FEATURE EXTRACTION BASED SVMS ARABIC TEXT CATEGORIZATION SYSTEM

Abdelwadood Moh’d A Mesleh

2007

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 classification system shows a high classification effectiveness for Arabic articles term of Macroaveraged F1 = 88.11 and Microaveraged F1 = 90.57.

Paper Citation

in Harvard Style

Moh’d A Mesleh A. (2007). CHI SQUARE FEATURE EXTRACTION BASED SVMS ARABIC TEXT CATEGORIZATION SYSTEM . In Proceedings of the Second International Conference on Software and Data Technologies - Volume 1: ICSOFT, ISBN 978-989-8111-05-0, pages 235-240. DOI: 10.5220/0001329402350240

in Bibtex Style

@conference{icsoft07,
author={Abdelwadood Moh’d A Mesleh},
title={CHI SQUARE FEATURE EXTRACTION BASED SVMS ARABIC TEXT CATEGORIZATION SYSTEM},
booktitle={Proceedings of the Second International Conference on Software and Data Technologies - Volume 1: ICSOFT,},
year={2007},
pages={235-240},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001329402350240},
isbn={978-989-8111-05-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Software and Data Technologies - Volume 1: ICSOFT,
TI - CHI SQUARE FEATURE EXTRACTION BASED SVMS ARABIC TEXT CATEGORIZATION SYSTEM
SN - 978-989-8111-05-0
AU - Moh’d A Mesleh A.
PY - 2007
SP - 235
EP - 240
DO - 10.5220/0001329402350240