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Semantic Relations Extraction and Ontology Learning from Arabic Texts—A Survey

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Intelligent Natural Language Processing: Trends and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 740))

Abstract

Semantic relations are the building blocks of the Ontologies and any modern knowledge representation system. Extracting semantic relations from the text is one of the most significant and challenging phases in the Ontology learning process. It is essential in all Ontology learning phases starting from building the Ontology from scratch, down to populating and enriching the existing Ontologies. It is challenging, on the other hand, as it requires dealing with natural language text, which represents various challenges especially for syntactically ambiguous languages such as Arabic. In this paper, we present a comprehensive survey of Arabic Semantic Relation Extraction and Arabic Ontology learning research areas. We study Arabic Ontology learning in general while focusing on Arabic Semantic Relation Extraction particularly, as being the most significant, yet challenging task in the Ontology learning process. To the best of our knowledge, this is the first work that addresses the process of Arabic Semantic Relation Extraction from the Ontology learning perspective. We review the conducted researches in both areas. For each research the used technique is illustrated, the limitations and the positive aspects are clarified.

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Notes

  1. 1.

    http://nooj4nlp.net/pages/resources.

  2. 2.

    http://globalwordnet.org/arabic-wordnet/.

  3. 3.

    http://www.nongnu.org/aramorph/.

  4. 4.

    http://www.undp.org.

  5. 5.

    http://www.hahooa.com/nav.php?ver=ar.

  6. 6.

    http://www.ars.usda.gov/Services/docs.htm?docid=8964.

  7. 7.

    https://fr.wikipedia.org/wiki/Sahih_al-Bukhari.

  8. 8.

    http://www.claes.sci.eg/coe_wm/kpminer/.

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Authors and Affiliations

  1. Faculty of Computers and Information Systems, Mansoura University, Mansoura, Egypt

    Aya M. Al-Zoghby, Aya Elshiwi & Ahmed Atwan

Authors
  1. Aya M. Al-Zoghby
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  2. Aya Elshiwi
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  3. Ahmed Atwan
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Corresponding author

Correspondence to Aya M. Al-Zoghby .

Editor information

Editors and Affiliations

  1. The British University in Dubai, Dubai, United Arab Emirates

    Khaled Shaalan

  2. Faculty of Computers and Information Technology, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  3. Faculty of Computers and Information, Ain Shams University, Cairo, Egypt

    Fahmy Tolba

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Al-Zoghby, A.M., Elshiwi, A., Atwan, A. (2018). Semantic Relations Extraction and Ontology Learning from Arabic Texts—A Survey. In: Shaalan, K., Hassanien, A., Tolba, F. (eds) Intelligent Natural Language Processing: Trends and Applications. Studies in Computational Intelligence, vol 740. Springer, Cham. https://doi.org/10.1007/978-3-319-67056-0_11

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  • DOI: https://doi.org/10.1007/978-3-319-67056-0_11

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