Exploring Qur’an by using Aspects and Dependencies

Abstract

The availability of intelligent data mining tools are vital to help explore and comprehend the religious text of Islam. In this paper we present the research background of a platform offering an illustrative graphic-based decision aid tool enabling Qur’an experts to easily detect links between the multiple aspects presented in the Qur’an. This tool not only links one chapter to another chapter, or one verse to another verse through words, but also connects chapters and verses together through concepts and dependencies. As such, the platform is a self-evolving platform, interconnecting data through their aspects and dependencies. The user can expand the database by adding new dependencies for example. The platform is an extendible Web application. We propose combining several tools, mainly Java and PhP. This platform combines neural network in data mining and TFIDF algorithms to analyze and filter Qua’ran’s content. The design of our approach is discussed and detailed.