Ontology-Based Semantic Retrieval for Museum News Systems

Introduction: Museums face challenges in managing and retrieving timely news content due to fragmented information systems. This study investigates how semantic web technologies can enhance contextual accuracy and accessibility in museum information retrieval.Methods: We created a domain-specific ontology integrated with relational databases via Ontology-Based Data Access (OBDA). A semantic search system accepting natural language queries was implemented and evaluated by experts using standard information retrieval metrics.Results: The system achieved strong performance with precision of 0,85, recall of 0,96, and F1-score of 0,88, demonstrating effective semantic retrieval of museum news.Conclusions: The findings demonstrate that semantic web technologies improve the accessibility and contextual relevance of museum news, contributing to digital heritage information management.