Tuberculosis Ontology Generation and Enrichment Based Text Mining

Abstract

Ontology is a knowledge representation model that used in the semantic web. To perform domain enrichment in the ontology needed a fast and efficient method, this can be achieved by using text mining approaches. This research was exacting text mining approach to enrich ontology in epidemiology domain, especially in tuberculosis. This study utilizes existing ontology, namely Epidemiology Ontology (EPO) and data from a variety of scientific documents about tuberculosis. The data obtained from scientific documents regarding tuberculosis (pulmonary TB) will be used to enrich Epidemiology Ontology (EPO). In this study enrichment is done semi-automatically, term and concept extraction is done automatically from a natural language corpus and validation is done manually by involving epidemiology experts.