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All Journal International Journal of Informatics and Communication Technology (IJ-ICT)
Abdelali Zbakh
Mohammed V University
Computer Science & IT

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Neural network dealing with Arabic language Adnan Souri; Mohammed Al Achhab; Badr Eddine Elmohajir; Abdelali Zbakh
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 9, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (411.072 KB) | DOI: 10.11591/ijict.v9i2.pp73-82

Abstract

Artificial Neural Networks have proved their efficiency in a large number of research domains. In this paper, we have applied Artificial Neural Networks on Arabic text to prove correct language modeling, text generation, and missing text prediction. In one hand, we have adapted Recurrent Neural Networks architectures to model Arabic language in order to generate correct Arabic sequences. In the other hand, Convolutional Neural Networks have been parameterized, basing on some specific features of Arabic, to predict missing text in Arabic documents. We have demonstrated the power of our adapted models in generating and predicting correct Arabic text comparing to the standard model. The model had been trained and tested on known free Arabic datasets. Results have been promising with sufficient accuracy.
Co-Authors Adnan Souri Badr Eddine Elmohajir Mohammed Al Achhab