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Article
Extracting semantic relations from the Quranic Arabic based on Arabic conjunctive patterns
Journal of King Saud University - Computer and Information Sciences
  • Rahima Bentrcia, Université Hadj Lakhdar de Batna
  • Samir Zidat, Université Hadj Lakhdar de Batna
  • Farhi Marir, Zayed University
Document Type
Article
Publication Date
7-1-2018
Abstract

© 2017 The Authors There is an immense need for information systems that rely on Arabic Quranic ontologies to provide a precise and comprehensive knowledge to the world. Since semantic relations are a vital component in any ontology and many applications in Natural Language Processing strongly depend on them, this motivates the development of our approach to extract semantic relations from the Quranic Arabic Corpus, written in Arabic script, and enrich the automatic construction of Quran ontology. We focus on semantic relations resulting from proposed conjunctive patterns which include two terms with the conjunctive AND enclosed in between. The strength of each relation is measured based on the correlation coefficient. Finally, we evaluate the significance of this method by using hypotheses testing and Student t-test. The obtained results are very promising since we combine an accurate Arabic grammar with strong statistical techniques to prove the existence and measure the strength of this type of semantic relations.

Publisher
King Saud bin Abdulaziz University
Keywords
  • Arabic AND conjunctive patterns,
  • Arabic grammar,
  • Ontology,
  • Quranic Arabic Corpus,
  • Semantic relations,
  • Text mining
Scopus ID

85029565976

Creative Commons License
Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International
Indexed in Scopus
Yes
Open Access
Yes
Open Access Type
Gold: This publication is openly available in an open access journal/series
Citation Information
Rahima Bentrcia, Samir Zidat and Farhi Marir. "Extracting semantic relations from the Quranic Arabic based on Arabic conjunctive patterns" Journal of King Saud University - Computer and Information Sciences Vol. 30 Iss. 3 (2018) p. 382 - 390 ISSN: <p><a href="https://v2.sherpa.ac.uk/id/publication/issn/1319-1578" target="_blank">1319-1578</a></p>
Available at: http://works.bepress.com/farhi-marir/8/