Quran content representation in NLP
Zineb Touati-Hamad, Mohamed Ridda Laouar, Issam Bendib · 2020
Word representation is a starting point for Natural Language Processing (NLP). These representations transform words into symbolic vectors of a given length that reveal the hidden linguistic and semantic similarities. This paper presents a study of the various word representation tools used for the content of the texts of the holy Quran in Arabic, which include the two main representation forms: Local representation and Distributed representation, with the aim of using them in different artificial intelligence subsets such as "machine learning" and "deep learning" algorithms that require NLP.