Arabic Text Summarization Challenges using Deep Learning Techniques: A Review

Main Article Content

Adnan Souri
Mohammed Al Achhab
Badr Eddine El Mohajir
Mohamed Naoum
Outman El Hichami
Abdelali Zbakh

Abstract

Text summarization is a challenging field in Natural Language Processing due to language modelisation and used techniques to give concise summaries.  Dealing with Arabic language does increase the challenge while taking into consideration the many features of the Arabic language, the lack of tools and resources for Arabic, and the Algorithms adaptation and modelisation. In this paper, we present several researches dealing with Arabic Text summarization applying different Algorithms on several Datasets. We then compare all these researches and we give a conclusion to guide researchers on their further work.

Article Details

How to Cite
Souri, A. ., Achhab, M. A. ., Mohajir, B. E. E. ., Naoum, M. ., Hichami, O. E. ., & Zbakh, A. . (2023). Arabic Text Summarization Challenges using Deep Learning Techniques: A Review. International Journal on Recent and Innovation Trends in Computing and Communication, 11(11s), 134–142. https://doi.org/10.17762/ijritcc.v11i11s.8079
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