The Role of Ontologies in Knowledge Representation Using Artificial Intelligence Techniques for Research and Retrieval Purposes

An Applied Study on Intellectual Output in the Field of Education

Abstract

The study examined ontologies as prominent knowledge representation tools to improve information retrieval systems using artificial intelligence, especially natural language processing. They aimed to enable systems to understand researchers’ queries more accurately and effectively. The study developed an ontological model for education using IBM Watson Knowledge Studio and integrated it with IBM Natural Language Understanding to improve referential search and retrieval. The research used both descriptive-analytical and experimental methods, applying the model to educational articles, websites, laws, regulations, and social media content to subtly extract entities, relationships, and thematic concepts. Findings showed that ontologies significantly enhance retrieval systems' efficiency by shifting from lexical matching to semantic understanding, thus improving search accuracy and understanding of specialized concepts. The study recommended expanding the use of ontologies and knowledge representation in Arabic, including these topics in library and information science curricula, and conducting future studies to integrate ontological models with advanced artificial intelligence for intelligent research and retrieval across knowledge fields.