Quran Intelligent Ontology Construction Approach Using Association Rules Mining
This work addresses the need for automated ontology construction in religious text analysis, specifically for the Quran, but it is incremental as it applies existing association rules and linguistic methods to a new domain.
The researchers tackled the problem of costly manual ontology construction from the Quran by developing an intelligent system that combines linguistic pattern-based methods and association rules mining to automatically extract concepts and semantic relations from Quran verses, resulting in a new ontology representation of Quran knowledge.
Ontology can be seen as a formal representation of knowledge. They have been investigated in many artificial intelligence studies including semantic web, software engineering, and information retrieval. The aim of ontology is to develop knowledge representations that can be shared and reused. This research project is concerned with the use of association rules to extract the Quran ontology. The manual acquisition of ontologies from Quran verses can be very costly; therefore, we need an intelligent system for Quran ontology construction using patternbased schemes and associations rules to discover Quran concepts and semantics relations from Quran verses. Our system is based on the combination of statistics and linguistics methods to extract concepts and conceptual relations from Quran. In particular, a linguistic pattern-based approach is exploited to extract specific concepts from the Quran, while the conceptual relations are found based on association rules technique. The Quran ontology will offer a new and powerful representation of Quran knowledge, and the association rules will help to represent the relations between all classes of connected concepts in the Quran ontology.