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Hybrid Segmentation Prototype for Arabic Text-Based Documents: Towards Plagiarism Detection

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  • Sonia Alouane-Ksouri

    (National Engineering School of Tunis, University of Tunis El Manar, Tunis, Tunisia)

  • Minyar Sassi Hidri

    (National Engineering School of Tunis, University of Tunis El Manar, Tunis, Tunisia)

Abstract

The contribution of this work relates to the field of Arabic text-based document analysis for the detection of plagiarism. This analysis will be carried out according to the triadic computation model of document similarity. The authors propose a hybrid segmentation prototype for Arabic text-based documents that links different processing steps in order to generate the similarity rate between the documents of an Arabic corpus. It involves two segmentation systems and a morphological analysis in order to obtain a matrix representation adapted to the triadic similarity computation according to three abstraction levels: documents, sentences and words.

Suggested Citation

  • Sonia Alouane-Ksouri & Minyar Sassi Hidri, 2015. "Hybrid Segmentation Prototype for Arabic Text-Based Documents: Towards Plagiarism Detection," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 6(1), pages 63-74, January.
    • Handle: RePEc:igg:jssmet:v:6:y:2015:i:1:p:63-74
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