Developing an Arabic-Urdu Ontology of Quranic Concepts: A Semantic Approach
Journal Title: International Journal of Innovations in Science and Technology - Year 2025, Vol 7, Issue 1
Abstract
An Arabic-Urdu ontology system dedicated to Quranic concepts represents a necessity for protecting the semantic value and making religious texts more accessible during Quranic study. Ontology-driven annotation tools show their ability to achieve precise translations and thematic searches by establishing their effects on the translation process. Researchers built this ontology using Protégé 5.6.4 which classifies Quranic concepts into twelve specific sections from Corpus.quran.com: Artifact, Astronomical Body, Event, False Deity, Holy Book, Language, Living Creation, Location, Physical Attribute, Physical Substance, Religion and Weather Phenomena. Validation of the ontology included expert evaluation and a HermiT computational assessment that led to user testing and an accuracy rate of 89.31%. The system uses SPARQL queries as a method to achieve both organized and efficient retrieval of Quranic knowledge. The analysis emphasizes the value of ontological structures as a means to connect Arabic and Urdu semantics which then improves both Quranic interpretation and computational linguistic understanding. While the methodology effectively maps Quranic concepts, challenges such as language nuances and theological precision persist, requiring further advancements in machine learning and natural language processing. Future research should focus on expanding ontology categories, integrating AIbased models, and enhancing phonetic mappings to improve the ontology’s adaptability and usability in diverse linguistic and cultural settings.
Authors and Affiliations
Fouzia Nadeem, Dr. Muhammad Arshad Awan, Muhammad Tariq, Danish Khaleeq
Impact of Internal Forces on Employee Behaviors: Role of Situational Factors
The current research investigated the effects of motivation, ability, and role perception (internal forces), also known as drivers on employee behaviors as well as to find out the moderating role of situational factors...
Machine Learning Prediction of Mechanical Properties in Reinforcement Bars: A Data-Driven Approach
Introduction/Importance of Study: This study addresses the pressing need for precise prediction of mechanical properties in steel reinforcement bars (rebars) through a data-driven approach utilizing machine learning te...
Comparative Evaluation of Machine Learning and Deep Learning Models for Real Estate Price Prediction
Accurate real estate price prediction is vital in informed decisionmaking for investors, policymakers, and stakeholders. This study evaluates various machine learning and deep learning models for predicting real estate...
Comprehensive Review on Postoperative Central Nervous System Infections (PCNSI): Causes, Prevention Strategies, and Therapeutic Approaches using Computer Based Electronic Health Record (EHR)
The central nervous system is susceptible to various infections. Over centuries, bacterial infections have proven lethal in various surgical procedures. Infections that occur after craniotomy are often due to the reope...
Vortex Powerplant Implementation in A Coastal Community
A gravitational water vortex power plant is an eco-friendly device that generates electricity from renewable energy sources. In this system, a turbine extracts energy from the vortex created by tangentially channeling...