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Automatic Arabic Text Summarization Approaches

by Samira Lagrini, Mohammed Redjimi, Nabiha Azizi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 164 - Number 5
Year of Publication: 2017
Authors: Samira Lagrini, Mohammed Redjimi, Nabiha Azizi
10.5120/ijca2017913628

Samira Lagrini, Mohammed Redjimi, Nabiha Azizi . Automatic Arabic Text Summarization Approaches. International Journal of Computer Applications. 164, 5 ( Apr 2017), 31-37. DOI=10.5120/ijca2017913628

@article{ 10.5120/ijca2017913628,
author = { Samira Lagrini, Mohammed Redjimi, Nabiha Azizi },
title = { Automatic Arabic Text Summarization Approaches },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 164 },
number = { 5 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 31-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume164/number5/27480-2017913628/ },
doi = { 10.5120/ijca2017913628 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:10:28.326772+05:30
%A Samira Lagrini
%A Mohammed Redjimi
%A Nabiha Azizi
%T Automatic Arabic Text Summarization Approaches
%J International Journal of Computer Applications
%@ 0975-8887
%V 164
%N 5
%P 31-37
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent years, automatic text summarization has seen renewed interest, and has been experiencing an increasing number of researches and products especially in English language. However, in Arabic language, little works and limited researches have been done in this field. This paper exposes a literature review of recent research works on Arabic text summarization. Current approaches used in this field are presented followed by a discussion about their limitations and the main challenges faced when dealing with such application. As a final point, a proposed approach to improve the quality of Arabic text summarization system is presented.

References
  1. Gupta, V. 2010. A survey of text summarization extractive techniques. J. Emerging Technologies in Web Intelligence, 2(3), 258-268.
  2. El-Shishtawy, T., El-Ghannam, F.2012.keyphrase based Arabic summarizer (KPAS). In informatics and systems (INFOS), 8th International Conference, IEEE.
  3. Radev, D.R. , Hovy, E., McKeown, K. 2002.Introduction to the special issue on Summarization. Computational linguistics, 28(4), 399-408.
  4. Lloret, E., Ferrandez, O., Munos, R. 2008. A Text summarization approach under the influence of textual entailment. In NLPCS, 22-31.
  5. Bawakid, A. 2011 Automatic documents summarization using ontology based methodologies. Doctoral Thesis. University of Birmingham.
  6. Mann, W.C. , Thompson, S. 1988. Rhetorical structure theory: toward a functional theory of text organization, Text-Interdisciplinary J. for the Study of Discourse, 8(3), 243-281.
  7. AlSanie, W. 2005 Towards an infrastructure for Arabic text summarization using rhetorical structure theory. Master's Thesis. King Saud University, Riyadh, Saudi Arabia.
  8. Mathkour, H. 2009. A Novel rhetorical structure approach for classifing Arabic security documents. J. Computer Theory and engineering, 1(3), 195.
  9. Azmi, A., Al-Thanyyan, S. 2012 .A Text summarizer for Arabic. J. Computer Speech and Language, 26(4), 260-273.
  10. Ibrahim, A., Elghazaly, T., Gheith, M. 2013. A Novel Arabic text summarization model based on rhetorical structure theory and vector space model. J. Computational Linguistique and Natural Language Processing, 2(8) , 480-485.
  11. Maaloul, M.H. 2012 Approche Hybride pour le Résumé Automatique de Textes Application à la langue arabe. Doctoral Thesis. Université de Provence-Aix-Marseille I, France.
  12. Asher, N., Lascarides, A.2003. Logics of conversation, Cambridge University Press .
  13. Keskes, I. 2015 Discourse analysis of arabic documents and application to automatic summarization. Doctoral Thesis. University of Toulouse III-Paul Sabatier.
  14. Oufaida, H., Nouali, O., Blache, P. 2014. Minimum redundancy and maximum relevance for single and multi-document Arabic text summarization. J. King Saud University-Computer and Information Sciences , 26(4), 450-461.
  15. Fejer, H.N., Omar, N. 2014. Automatic Arabic text summarization using clustering and keyphrase extraction. In Information Technology and Multimedia (ICIMU), 293-298.
  16. Haboush, A., Al-zoubi, M. 2012. Arabic text summarization model using clustering techniques. J. Word of Computer Science and Information Technology (WCSIT), 2221-0741.
  17. El-Haj, M., Kruschwitz, U., Fox, C.2011. Exploring clustering for multi-document arabic summarisation. In Asia Information Retrieval Symposium, Springer Berlin Heidelberg. 550-561.
  18. Sobh, I.M.A.H. 2009 An optimized dual classification system for Arabic extractive generic text summarization, Doctoral Thesis. Faculty of engineering,Cairo university, Giza, Egypt.
  19. Abdel Fattah, M., Ren,F. 2009 . GA, MR, FFNN, PNN and GMM based models for automatic text summarization. Computer Speech & Language , 23(1), 126-144.
  20. Belkebir, R., Guessoum, A. 2015. A supervised approach to Arabic text summarization using adaboost. New contributions in information systems and technologies, Springer International Publishing, 227–236.
  21. Al-Taani, A.T. , Maha, M. 2014 .An extractive graph-based Arabic text summarization approach.
  22. Imam, I., Nounou, N., Hamouda, A., Abdul Khalek, H. 2013. An ontology-based summarization system for arabic documents (ossad). J. computer application(IJCA), 74(17).
  23. Al-Khawaldeh, F., Samawi, V.W. 2015. Lexical cohesion and entailment based segmentation for Arabic text summarization(LCEAS) .J. the Word of Computer Science and Information Technology, 5(3), 51-60.
  24. Tatar, D., Mihis, A., Lupsa, D. 2009. Entailment based linear segmentation in summarization. J. Software Engineering and Knowledge Engineering, 19(08), 1023-1038.
  25. Khalifa, I., Feki, Z. and Farawila, A. 2011. Arabic Discourse Segmentation Based on Rhetorical Methods. Int. J. Electric Comput. Sci, 11(1), 10-15.
  26. Lloret, E., Palomar, M. 2012.Text summarisation in progress: a literature review. Artificial Intelligence Review, 37(1),1-41.
  27. Feng, V.W. 2015 RST-Style Discourse Parsing and Its Applications in Discourse Analysis. Doctoral Thesis. University of Toronto, Canada.
Index Terms

Computer Science
Information Sciences

Keywords

Arabic text summarization clustering RST machine learning graph theory text entailment extractive approaches.

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