ONTOLOGY-DRIVEN CONTEXTUAL SEARCH AND RECOMMENDATION SYSTEM FOR NAVIGATING BIBLIOGRAPHIC METADATA IN INTELLIGENT INFORMATION SYSTEMS

The growing volume of bibliographic metadata, such as books, and journal articles, has made it increasingly difficult for users to locate relevant resources efficiently. Traditional search engines often return an overwhelming number of results, many of which are irrelevant, leading to frustration and wasted time. Ontologies help structure and organize complex bibliographic data by defining relationships between concepts, while contextual search algorithms enhance the system’s ability to understand user intent. This paper presents the implementation of an ontology-based contextual search and recommendation system within the GujCat portal, specifically focusing on the search functionality. Our system uses ontology mapping for linking knowledge frameworks for consistency and SPARQL Protocol and RDF Query Language (SPARQL) to enhance search capabilities. This solution helps users easily locate specific resources and discover related materials that might otherwise be overlooked. This work underscores the potential of ontology-driven frameworks in academic and research environments, offering a robust solution for metadata management and resource accessibility.