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Considering the progress of Artificial Intelligence (AI) and the Information Technology (IT) we witness, during recent years, the spread of the application of these technologies in various fields. The research workflows, and in particular, the researches on Islamic sciences are not excepted from this issue. Several works have been carried out in order to exploit the AI and modern information technologies in the researches on Islamic sciences during recent years all over the Islamic regions and beyond them. It is very important to be aware of the latest developments in this field from different aspects like: 1) Benefiting from the advantages of modern technologies in the Islamic researches, 2) Reorganizing the educational plans in accordance with these developments, and 3) Introducing the new applications of AI in Islamic studies to the academics of computer sciences who may be interested in this field. In this paper, in the first step, a systematic review was conducted concerning more than four thousand international scientific articles related to applying AI and modern IT in Islamic studies, out of which 975 ones were chosen. At the same time, major institutions in this field were identified. In the next step the selected articles were classified in five thematic fields of 1) the Holy Qur’an, Tafsir and other related issues, 2) Hadith and Rijal Sciences, 3) Islamic Law and Jurisprudence, 4) the General Islamic Content in Social Media, 5) Other Subjects related to Islamic Sciences like Linguistics, History, Geography, etc. In the third step, the articles of each category were classified in a number of major subcategories that amount to 73 in total. Finally, in the last step, the distinctive articles in each field were introduced briefly.
Considering the progress of Artificial Intelligence (AI) and the Information Technology (IT) we witness, during recent years, the spread of the application of these technologies in various fields. The research workflows, and in particular, the researches on Islamic sciences are not excepted from this issue. Several works have been carried out in order to exploit the AI and modern information technologies in the researches on Islamic sciences during recent years all over the Islamic regions and beyond them. It is very important to be aware of the latest developments in this field from different aspects like: 1) Benefiting from the advantages of modern technologies in the Islamic researches, 2) Reorganizing the educational plans in accordance with these developments, and 3) Introducing the new applications of AI in Islamic studies to the academics of computer sciences who may be interested in this field. In this paper, in the first step, a systematic review was conducted concerning more than four thousand international scientific articles related to applying AI and modern IT in Islamic studies, out of which 975 ones were chosen. At the same time, major institutions in this field were identified. In the next step the selected articles were classified in five thematic fields of 1) the Holy Qur’an, Tafsir and other related issues, 2) Hadith and Rijal Sciences, 3) Islamic Law and Jurisprudence, 4) the General Islamic Content in Social Media, 5) Other Subjects related to Islamic Sciences like Linguistics, History, Geography, etc. In the third step, the articles of each category were classified in a number of major subcategories that amount to 73 in total. Finally, in the last step, the distinctive articles in each field were introduced briefly.
The research presented in the following paper focuses on the effectiveness of a modern standard Arabic corpus, AraFast, in training transformer models for natural language processing tasks, particularly in Arabic. In the study described herein, four experiments were conducted to evaluate the use of AraFast across different configurations: segmented, unsegmented, and mini versions. The main outcomes of the present study are as follows: Transformer models trained with larger and cleaner versions of AraFast, especially in question-answering, indicate the impact of corpus quality and size on model efficacy. Secondly, a dramatic reduction in training loss was observed with the mini version of AraFast, underscoring the importance of optimizing corpus size for effective training. Moreover, the segmented text format led to a decrease in training loss, highlighting segmentation as a beneficial strategy in Arabic NLP. In addition, using the study findings, challenges in managing noisy data derived from web sources are identified, which were found to significantly hinder model performance. These findings collectively demonstrate the critical role of well-prepared, segmented, and clean corpora in advancing Arabic NLP capabilities. The insights from AraFast’s application can guide the development of more efficient NLP models and suggest directions for future research in enhancing Arabic language processing tools.
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