A Knowledge-Based Approach for Provisions’ Categorization in Arabic Normative Texts

  • Ines BerrazegaEmail author
  • Rim Faiz
  • Asma Bouhafs
  • Ghassan Mourad
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 464)


This paper studies the problem of automatic categorization of provisions in Arabic normative texts. We propose a knowledge-based categorization approach coupling a taxonomy of Arabic normative provisions’ categories, an Arabic normative terminological base and a rule-based semantic annotator. The obtained model has been trained and tested over a collection of Arabic normative texts collected from the Official Gazette of the Republic of Tunisia. The performance of the approach was evaluated in terms of Precision, Recall and F-score in order to categorize instances over 14 normative categories. The obtained results over the test dataset are very promising. We have obtained 96.4 % for Precision, 96.06 % for Recall and 96.23 % for F-score.


Natural language processing Semantic annotation Information extraction Arabic language Normative provisions 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ines Berrazega
    • 1
    Email author
  • Rim Faiz
    • 2
  • Asma Bouhafs
    • 3
  • Ghassan Mourad
    • 4
  1. 1.LARODECUniversity of Tunis – ISGBardoTunisia
  2. 2.LARODECUniversity of Carthage – IHECCarthage PresidencyTunisia
  3. 3.University of Carthage – IHECCarthage PresidencyTunisia
  4. 4.CSLCLebanese UniversityBeirutLebanon

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