Abstract
The exploration of Hadith sciences gains significant consideration over the most recent couple of years. Hadith is mostly the sayings of Prophet Mohammad. The Holy Quran represents the first origin of law in Islam then Hadith takes the second role. Many research efforts manage Hadith with respect to the “Isnad” and “Matn”; which are the main two pieces of Hadith. In this paper, we examine the chance of utilizing Deep Learning to process Isnad of Hadiths. Consequently, a definitive objective of our framework is to help in the systematic classification of Hadiths and differentiate among the correct (“Sahih”) Hadiths and the not accurate (“Da'ief”) Hadiths.
Highlights
There are a lot of concepts and techniques used by researchers and specialist to find the most ideal means that people can interface with PCs, Artificial Intelligence (AI) is one of these efforts
Machine learning relies on algorithms that can be fed with structured data and analyzes it to reach conclusions, while deep learning is characterized by the presence of different levels of algorithms that form artificial neural networks (ANNs) that have the ability to understand unorganized data and complex patterns, such as languages, pictures and speech
Deep learning is an approach that could be used in text classification, so, in this paper we will investigate the opportunity of using deep learning to classify Hadiths to the correct (“Sahih”) and the not accurate (“Da'ief”) Hadiths
Summary
There are a lot of concepts and techniques used by researchers and specialist to find the most ideal means that people can interface with PCs, Artificial Intelligence (AI) is one of these efforts. Consider the following example (Hadith1), which is narrated in “Sahih Muslim” book [5]: َ َع ْن ِع ْك ِر َمة، قَا َل أَ ْخبَ َرنَا َح ْن َظلَةُ ْب ُن أَبِي ُس ْفيَا َن،”
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