Automatic Arabic text summarization based on fuzzy logic

Lamees M. Al Qassem, Di Wanga, Hassan Barada, Ahmad Al Rubaiea, Nawaf Al Moosaa

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

The unprecedented growth in the amount of online information available in many languages to users and businesses, including news articles and social media, has made it difficult and time consuming for users to identify and consume sought after content. Hence, automatic text summarization for various languages to generate accurate and relevant summaries from the huge amount of information available is essential nowadays. Techniques and methodologies for automatic Arabic text summarization are still immature due to the inherent complexity of the Arabic language in terms of both structure and morphology. This work attempts to improve the performance of Arabic text summarization. We propose a new Arabic text summarization approach based on a new noun extraction method and fuzzy logic. The proposed summarizer is evaluated using EASC corpus and benchmarked against popular state of the art Arabic text summarization systems. The results indicate that our proposed Fuzzy logic approach with noun extraction outperforms existing systems.

Original languageBritish English
Title of host publicationICNLSP 2019 - Proceedings of the 3rd International Conference on Natural Language and Speech Processing
Pages42-48
Number of pages7
ISBN (Electronic)9781950737628
StatePublished - 2019
Event3rd International Conference on Natural Language and Speech Processing, ICNLSP 2019 - Trento, Italy
Duration: 12 Sep 201913 Sep 2019

Publication series

NameICNLSP 2019 - Proceedings of the 3rd International Conference on Natural Language and Speech Processing

Conference

Conference3rd International Conference on Natural Language and Speech Processing, ICNLSP 2019
Country/TerritoryItaly
CityTrento
Period12/09/1913/09/19

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