Review Article
Volume 2 Issue 2
Ahmed Samir Ahmed Ibrahim El khadrawy*, Safia Abbas, Yasser Kamal Omar and Nady Hussain Abd Jawad
January 07, 2023
Abstract
There is a huge shortage of scientific research in the Arabic language, especially in natural language processing and relationships between Arabic documents and other specific documents. This shortage is also reflected in Arabic Books' introduction, Topics abstraction, and content summary engines. Furthermore, there are some good samples of Arabic words inside the Quran. The Quran is the holy book of Islam, that is divided into chapters (surah) and verses (ayat) of differing lengths and topics. This paper introduces a framework for both specialized researchers in Islamic studies as well as non-specialized researchers to find hidden relationships between one of the most important chapters of the Holy Quran which is Al Fatiha surah and the remaining chapters of the Holy Quran using Hierarchical Technique data modeling as an unsupervised learning technique. a new framework that can access tokens of the Holy Quran in different granule parts such as chapter (sura) part of the chapter (Aya) of the Holy Quran Sura, words, word roots, Aya roots, and Aya meaning in the Arabic language, Moreover, We had developed a lot of statistics related to Fatiha Sura and the holy Quran like (roots distinct for every Sura, Words Redundancy, Roots Redundancy, Matrix report by roots and every sura, Matrix report shows Percentage of roots similarity by every sura and whole Quran distinct roots, etc.). Furthermore, we enhance the search engine results by adding search by roots and Aya meaning for every Sura. And the results for sample queries show accuracy with more than 3% using meaning and roots compared to the text of the Holy Quran only.
Keywords: holy Quran text Analysis; Text Mining; Arabic Text Mining; 1N Form; 2Nform; Data Modeling; holy Quran Tafseer text