research-article

The Contribution of Stemming and Semantics in Arabic Topic Segmentation

Authors:

Anja Habacha Chaibi,

Henda Hajjami Ben GhezalaAuthors Info & Claims

ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Volume 17, Issue 2

Article No.: 12, Pages 1 - 25

https://doi.org/10.1145/3152464

Published: 11 January 2018 Publication History

Abstract

Topic Segmentation is one of the pillars of Natural Language Processing. Yet there is a remarkable research gap in this field, as far as the Arabic language is concerned. The purpose of this article is to improve Arabic Topic Segmentation (ATS) by inquiring into two segmenters: ArabC99 and ArabTextTiling. This study is carried out on two independent levels: the pre-processing level and the segmentation level. These levels represent the basic steps of topic segmentation. On the pre-processing level, we examine the effect of using different Arabic stemming algorithms on ATS. We find out that Light10 is more appropriate for the pre-processing step. Based on this conclusion, we proceed to the second level by proposing two Arabic segmenters called ArabC99-LS-LSA and ArabTextTiling-LS-LSA. These latter use external semantic knowledge related to the Latent Semantic Analysis (LSA). Based on the evaluation results, we notice that LSA provides improvements in this field. Hence, the main outcome of this article emphasizes the multilevel improvement of ATS based on Light10 and LSA.

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Cited By

Zerrouki T(2024)Tashaphyne: A Python package for Arabic Light StemmingJournal of Open Source Software10.21105/joss.060639:93(6063)Online publication date: Jan-2024
https://doi.org/10.21105/joss.06063
Bahloul BAliane HBenmohammed M(2020)ArA*summarizer: An Arabic text summarization system based on subtopic segmentation and using an A* algorithm for reductionExpert Systems10.1111/exsy.1247637:2Online publication date: 15-Jan-2020
https://doi.org/10.1111/exsy.12476

Index Terms

The Contribution of Stemming and Semantics in Arabic Topic Segmentation
1. Information systems
  1. Information retrieval
    1. Document representation
      1. Content analysis and feature selection

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Published In

cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 17, Issue 2

June 2018

134 pages

ISSN:2375-4699

EISSN:2375-4702

DOI:10.1145/3160862

Editor:
Nianwen Xue
Brandeis University, Waltham, USA

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Publication History

Published: 11 January 2018

Accepted: 01 October 2017

Revised: 01 August 2017

Received: 01 October 2016

Published in TALLIP Volume 17, Issue 2

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Cited By

Zerrouki T(2024)Tashaphyne: A Python package for Arabic Light StemmingJournal of Open Source Software10.21105/joss.060639:93(6063)Online publication date: Jan-2024
https://doi.org/10.21105/joss.06063
Bahloul BAliane HBenmohammed M(2020)ArA*summarizer: An Arabic text summarization system based on subtopic segmentation and using an A* algorithm for reductionExpert Systems10.1111/exsy.1247637:2Online publication date: 15-Jan-2020
https://doi.org/10.1111/exsy.12476

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