Arabic Text Classification: A Review Study on Feature Selection Methods

被引：0

作者：

Hijazi, Musab Mustafa ^{[1
]}

Zeki, Akram ^{[2
]}

Ismail, Amelia ^{[3
]}

机构：

[1] Al Ain Univ, Dept Software Engn & Comp Sci, Coll Engn, Al Ain, U Arab Emirates

[2] Int Islamic Univ Malaysia, Dept Informat Technol, Kulliyyah Informat & Commun Technol, Kuala Lumpur, Malaysia

[3] Int Islamic Univ, Dept Comp Sci, Kulliyyah Informat & Commun Technol, Kuala Lumpur, Malaysia

来源：

2021 22ND INTERNATIONAL ARAB CONFERENCE ON INFORMATION TECHNOLOGY (ACIT) | 2021年

关键词：

Arabic Text Classification; Feature selection; Wrapper selection; filter method; ARTIFICIAL BEE COLONY;

D O I：

10.1109/ACIT53391.2021.9677185

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The list of features and text representation model that is utilized are critical components that determine the performance and accuracy of text categorization. Feature selection is a technique for improving classification accuracy and processing efficiency by removing redundant or superfluous words (features) and keeping only those that give vital information that assists in categorization. This paper presents the recent researches that studied the impact of feature selection methods on Arabic text classification.

引用

页码：554 / 559

页数：6

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