Multi-Label Arabic Text Classification: An Overview

被引:0
作者
Aljedani, Nawal [1 ]
Alotaibi, Reem [1 ]
Taileb, Mounira [1 ]
机构
[1] King Abdulaziz Univ, Fac Comp & Informat Technol, Jeddah, Saudi Arabia
关键词
Machine learning; text classification; multi-label classification; Arabic natural language processing; hierarchical classification; Lexicon approach; ALGORITHMS; TREES;
D O I
10.14569/IJACSA.2020.0111086
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
There is a massive growth of text documents on the web. This led to the increasing need for methods that can organize and classify electronic documents (instances) automatically. Multi-label classification task is widely used in real-world problems and it has been applied on different applications. It assigns multiple labels for each document simultaneously. Few and insufficient research studies have investigated the multi-label text classification problem in the Arabic language. Therefore, this survey paper aims to present an extensive review of the existing multi-label classification methods and techniques that can deal with multi-label problem. Besides, we focus on Arabic language by covering the relevant applications of multi-label classification on the Arabic text, and identify the main challenges faced by these studies. Furthermore, this survey presents an experimental comparisons of different multi-label classification methods applied for the Arabic context and points out some baseline results. We found that further investigations are also needed to improve the multi-label classification task in the Arabic language, especially the hierarchical classification task.
引用
收藏
页码:694 / 706
页数:13
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