Extracting a domain ontology from linguistic resource based on relatedness measurements

Creating domain-specific ontologies is one of the main bottlenecks in the development of the semantic Web. Learning an ontology from linguistic resources is helpful to reduce the costs of ontology creation. In this paper, we describe a method to extract the most related concepts from HowNet, a Chinese-English bilingual knowledge dictionary, in order to create a customized ontology for a particular domain. We introduce a new method to measure relatedness (rather than similarity between concepts), which overcomes some of the traditional problems associated with similar concepts being far apart in the hierarchy. Experiments show encouraging results.