Building ontology based-on heterogeneous data

Abstract

Ontologies play an important role in the distinct areas, such as information retrieval, information extraction, question and answer. They help us in capturing and storing knowledge in a particular domain and can be used for distinct applications. In recent years, research relevant to ontology development has produced tangible results concerning semantic web, information extraction, etc. In this paper, a domain specific ontology called Information Technology Ontology (ITO) is proposed. This ontology is built basing on three distinct sources of Wikipedia, WordNet and ACM Digital Library. An information extraction system focusing on computing domain based on this ontology in the future will be built. In order to have an ontology with highest quality and performance as expected, the authors combine some algorithms between machine learning and natural language processing (NLP) for building ontology. Results generated by such experiments show that these algorithms outperform others, especially in semantic relations among entities of ontology.