Application of a Question Answering System in the Ontology-Based Health Domain and Question Templates to Improve the Quality of Answers

Yudhono, Efwandha
Shaufiah, Shaufiah
Sardi, Indra Lukmana

Journal La Multiapp
Vol. 5 No. 5 (2024): Journal La Multiapp

Developing an effective Question Answering System (QAS) to address a wide range of health-related inquiries presents a significant challenge. This study introduces an innovative approach using an ontology-based QAS within the health domain, leveraging the Resource Description Framework (RDF) and SPARQL query language. By utilizing ontology, the system can more accurately map health concepts, improving the relevance and precision of its responses. Additionally, the incorporation of structured Question Templates enhances the system’s ability to understand and respond to diverse user queries. The system's performance was evaluated using Black Box Testing, which demonstrated that it consistently provides accurate and relevant answers. The system achieved a Mean Average Precision (MAP) of 79.6%, indicating its potential to effectively address a broad spectrum of health issues.