An automatic approach for bilingual tuberculosis ontology based on ontology design patterns (ODPs)

Abstract

Ontology is a representation term used to describe and represent a domain of knowledge. Manually ontology development is currently considered complex, requiring a lot of time and effort. This research was proposed to develop methods to build automatic domain ontology bilingual in Indonesian and English by using corpus and ontology design patterns (ODPs) in tuberculosis disease. In this study, the methods used were to combine ontology learning from text and ontology design patterns to decrease the role of expert knowledge. The methods in this research consist of six stages are term and relation extraction, matching with Tuberculosis glossary, matching with ODPs, score computation similarity term and relations with ODPs, ontology building and ontology evaluation. The results of ontology construction were 362 terms and 44 relations with 260 terms were added. The calculation accuracy of ontology construction was 71%. Ontology construction had higher complexity and shorter time as well as decreases the role of the expert knowledge which proof that the automatic ontology evaluation is better than manual ontology construction.