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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Deep Learning Model for Identifying the Arabic Language Learners based on Gated Recurrent Unit Network

Author 1: Seifeddine Mechti Author 2: Roobaea Alroobaea Author 3: Moez Krichen Author 4: Saeed Rubaiee Author 5: Anas Ahmed
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 11, No. 5 · Published 2020

DOI: https://doi.org/10.14569/IJACSA.2020.0110576

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Abstract

This paper focuses on identifying the Arabic Lan-guage learners. The main contribution of the proposed method is to use a deep learning model based on the Gated Recurrent Unit Network (GRUN). The proposed model explores a multitude of stylistic features such as the syntax, the lexical and the n-grams ones. To the best of our awareness, the obtained results outperform those obtained by the best existing systems. Our accuracy is the best comparing with the pioneers (45% vs 41%), considering the limited data and the unavailability of accurate tools dedicated to the Arabic language.

Keywords

Arabic Native Language Identification (NLI) deep learning Gated Recurrent Unit Network (GRUN)

How to Cite this Article

Mechti, S., Alroobaea, R., Krichen, M., Rubaiee, S., & Ahmed, A. (2020). Deep Learning Model for Identifying the Arabic Language Learners based on Gated Recurrent Unit Network. International Journal of Advanced Computer Science and Applications, 11(5). https://doi.org/10.14569/IJACSA.2020.0110576

Mechti, Seifeddine, et al.. "Deep Learning Model for Identifying the Arabic Language Learners based on Gated Recurrent Unit Network." International Journal of Advanced Computer Science and Applications, vol. 11, no. 5, 2020, https://doi.org/10.14569/IJACSA.2020.0110576.

@article{Mechti2020,
  title     = {Deep Learning Model for Identifying the Arabic Language Learners based on Gated Recurrent Unit Network},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {5},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Seifeddine Mechti and Roobaea Alroobaea and Moez Krichen and Saeed Rubaiee and Anas Ahmed},
  doi       = {10.14569/IJACSA.2020.0110576},
  url       = {https://doi.org/10.14569/IJACSA.2020.0110576}
}

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