Work

Ontology-Based Semantic Retrieval for Museum News Systems

Year: 2025

Type: article

Abstract: 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.

Source: Data & Metadata

DOI: 10.56294/dm20251147

Authors: Supavit Phuvarit, Pongsathon Pookduang, Rapeepat Klangbunrueang, Sumana Chiangnangam, Wirapong Chansanam, Kulthida Tuamsuk, Tassanee Lunrasri

Institutions: Khon Kaen University, Rajamangala University of Technology Isan, Rajamangala University of Technology Isan, Khon Kaen Campus

Language: English

Topic: Semantic Web and Ontologies

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4413331965

FWCI:

Cites: 15

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Related to: 10