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Pedagogical Indexed Arabic Text in Cloud E-Learning System

Author

Listed:
  • Nafaa Haffar

    (University of Monastir, Monastir, Tunisia)

  • Mohsen Maraoui

    (LaTice Lab, Faculty of Sciences of Monastir, University of Monastir, Monastir, Tunisia)

  • Shadi Aljawarneh

    (Jordan University of Science and Technology, Faculty of Computer and Information Technology, Irbid, Jordan)

  • Mohammed Bouhorma

    (Abdelmalek Essaâdi University, Tétouan, Morocco)

  • Abdallah Altahan Alnuaimi

    (Al-Isra University, Amman, Jordan)

  • Bilal Hawashin

    (Al-Zaytoonah University, Amman, Jordan)

Abstract

The Cloud E-Learning Systems for the Arabic language are relevant environments in many areas of training (teaching Arabic language) but also pose problems related to their creation tedious, costly in resources and time, and problems related to the search for information because of the increasing amount of information available and because of the methods of indexing, which is based on static methods such as keyword search that makes irrelevant the research process. For this, a new method of indexation is required. In this paper, a new Arabic text is proposed indexing approach using the creation of a new application profile of the LOM metadata schema (Learning Object Metadata) for the Arabic language. This profile includes the fields of LOM standard, and adds new fields for specific search information to Arabic language, and meets the needs of a teacher. Also, it's all using natural language processing tools like SAPA and AL-KHALIL.

Suggested Citation

  • Nafaa Haffar & Mohsen Maraoui & Shadi Aljawarneh & Mohammed Bouhorma & Abdallah Altahan Alnuaimi & Bilal Hawashin, 2017. "Pedagogical Indexed Arabic Text in Cloud E-Learning System," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 7(1), pages 32-46, January.
    • Handle: RePEc:igg:jcac00:v:7:y:2017:i:1:p:32-46
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