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DOI: 10.14569/IJACSA.2023.0140543
PDF

New Arabic Root Extraction Algorithm

Author 1: Nisrean Jaber Thalji
Author 2: Emran Aljarrah
Author 3: Roqia Rateb
Author 4: Amaal Rateb Mohammad Al-Shorman

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 5, 2023.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: This research presents a new algorithm for Arabic root extraction, which aims to improve the accuracy of Arabic Natural Language Processing Algorithms by addressing the weaknesses and errors of existing algorithms. The proposed algorithm utilizes a database, that includes a collection of roots, patterns, and affixes, to generate potential derivation roots of a word without eliminating affixes initially. By matching the derived word with patterns to identify potential roots, the proposed algorithm avoids the inaccuracies caused by eliminating affixes based on expectation methods. The study conducted a comparison of the proposed algorithm with three commonly used Arabic root extraction algorithms. The evaluation process is performed on three corpora. Results showed that the proposed algorithm achieved an average accuracy rate of 96%, which is significantly higher than the others.

Keywords: Natural language processing; Arabic root extraction algorithm; Arabic applications; Arabic morphology; Text mining

Nisrean Jaber Thalji, Emran Aljarrah, Roqia Rateb and Amaal Rateb Mohammad Al-Shorman, “New Arabic Root Extraction Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 14(5), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140543

@article{Thalji2023,
title = {New Arabic Root Extraction Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140543},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140543},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {5},
author = {Nisrean Jaber Thalji and Emran Aljarrah and Roqia Rateb and Amaal Rateb Mohammad Al-Shorman}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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