Abstract
The Holy Quran is one of the holy books revealed to the prophet Muhammad in the form of separate verses. These verses were written on tree leaves, stones, and bones during his life; as such, they were not arranged or grouped into one book until later. There is no intelligent system that is able to distinguish the verses of Quran chapters automatically. Accordingly, in this study we propose a model that can recognize and categorize Quran verses automatically and conclusion the essential features through Quran chapters classification for the first six Surat of the Holy Quran chapters, based on machine learning techniques. The classification of the Quran verses into chapters using machine learning classifiers is considered an intelligent task. Classification algorithms like Naive Bayes, SVM, KNN, and decision tree J48 help to classify texts into categories or classes. The target of this research is using machine learning algorithms for the text classification of the Holy Quran verses. As the Quran texts consists of 114 chapters, we are only working with the first six chapters. In this paper, we build a multi-class classification model for the chapter names of the Quranic verses using Support Vector Classifier (SVC) and GaussianNB. The results show the best overall accuracy is 80% for the SVC and 60% for the Gaussian Naive Bayes.
Highlights
Text classification of the Holy Quran is a research topic researchers should pay attention to in the context of machine learning algorithms.The Holy Quran is a book that was sent down from the heavens into the heart of the prophet Muhammad to be delivered to all human beings, Muslims
We have previously studied the architecture of the Arabic Language Sentiment Analysis (ALSA) [1]
The study detailed in [2] proposed an automation model that could classify Al-hadeeth features into Sahih, Hasan, Da’if, and Maudu, using machine learning techniques (LinearSVC, SGDClassifier, and LogisticRegression)
Summary
Text classification of the Holy Quran is a research topic researchers should pay attention to in the context of machine learning algorithms. The sacred words were revealed by Allah and written into a meaningful textual format that could be analysed and classified using machine learning classification algorithms. It is considered a comprehensive book covering every component of life and accessible to all people. Multi-class classification means that we need an automating model that enables classification of the texts For this reason, this paper looks at the first six chapters from the Holy Quran; its approximately 1000 verses contain a total 8000 features for the training and testing data. This paper is constructed as follows: the section presents related work on multi-class text classification of the Holy Quran. The fourth section includes the results followed by the conclusions and anticipations of future work
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