An automatic arabic text summarization system based on genetic algorithms

被引：5
|
作者：
Tanfouri, Imen [1 ]
Tlik, Ghassen [1 ,2 ]
Jarray, Fethi [1 ,2 ]
机构：
[1] UTM Univ, LIMTIC Lab, Tunis, Tunisia
[2] Higher Inst Comp Sci Medenine, Tunis, Tunisia
来源：
AI IN COMPUTATIONAL LINGUISTICS | 2021年 / 189卷
关键词：
single document summarization; arabic text; genetic algorithm; natural language processing; SINGLE;
D O I：
10.1016/j.procs.2021.05.083
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Text summarization is the creation of compressed version of a given document that covers important information from original document. The aim of text summarization is to reduce the original text into a shorter text which represents significant content of the original text. There are two approaches for automatic text summarization: extractive and abstractive. Extractive summarization consists to select the most significant sentences on the original text. Abstractive summarization consists to compose novel sentences coherent with the original text. In this paper, we present an extractive based single document approach for Arabic text summarization system using Genetic Algorithms. (C) 2021 The Authors. Published by Elsevier B.V.
引用
收藏
页码：195 / 202
页数：8
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