Abstract
Arabic documents are massively rising due to numerous contents utilized in websites, social media, and news articles. The classification of such documents in labelled categories is a significant and vital task that deserves more attention. Arabic Text Classification is an emerging research theme in Arabic Natural Language Processing. Recently, Deep Neural Network approaches have successfully been applied to many text classification problems, especially in English Text Classification. Convolutional Neural Network (CNN) is one of the best popular models. However, CNN is not highly applied in Arabic Text Classification. In addition, the recent studies did not achieve a high classification accuracy due to parameter setting issue. To overcome this limitation, a new hybrid classification model for Arabic Text is developed. This paper proposes Genetic Algorithms based Convolutional Neural Network for Arabic Text Classification. Genetic Algorithm is used to optimize the CNN parameters. The proposed model is tested using two large datasets and compared with the state-of-the art studies. The results showed that the classification accuracy achieved an improvement of 4 to 5%.
Highlights
T HE Arabic language is the second hardest language and the fifth most used language around the world [1]
This study presents a new classification model for Arabic text based on Deep Learning (DL)
Convolutional Neural Network is one of most common DL algorithm that has successfully been applied to many domains including Arabic Natural Language Processing (ANLP), for example in Text Classification ( [6], [7]) and sentiment analysis ( [13], [14], [15])
Summary
T HE Arabic language is the second hardest language and the fifth most used language around the world [1]. This study presents a new classification model for Arabic text based on Deep Learning (DL). Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS a new hybrid classification model for Arabic text based on CNN and Genetic Algorithm (GA). To the best of our knowledge, even though the optimization methods were proved to enhance the Deep Learning results ( [16] [17]), it has not been yet applied for Arabic text classification. 1)- Propose a new hybrid Arabic text classifier based on Genetic Algorithm and Convolutional Neural Networks. The proposed model is compared with a baseline, defined to be the Arabic text classification using CNN without parameter setting process, in addition to the state-of-the-art studies. This study presents a pioneering hybrid method for Arabic text classification using GA based CNN.
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