Comparative Study of Arabic Stemming Algorithms for Topic Identification

被引：7
|
作者：
Naili, Marwa [1 ]
Chaibi, Anja Habacha [1 ]
Ben Ghezala, Henda Hajjami [1 ]
机构：
[1] Univ Manouba, Natl Sch Comp Sci ENSI, RIADI Lab, Manouba 2010, Tunisia
来源：
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KES 2019) | 2019年 / 159卷
关键词：
Arabic Stemming algorithms; LDA; Topic identification;
D O I：
10.1016/j.procs.2019.09.238
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Stemming process is one of the important pre-processing steps in different natural language process tasks such as text mining and information retrieval. Yet, stemming process can be considered as a difficult step to realize according to the used language. In fact, due to the complex morphology of Arabic language, stemming results can be influenced. Thus, several algorithms have been proposed in order to overcome stemming problems. In this paper, we investigate different stemming algorithms by presenting a comparative study in the field of Arabic topic identification. (C) 2019 The Authors. Published by Elsevier B.V.
引用
收藏
页码：794 / 802
页数：9
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