Extracting a Domain Ontology from Linguistic Resource Based on Relatedness Measurements

Authors:
Ting Wang;Diana Maynard;Wim Peters;Kalina Bontcheva;Hamish Cunningham
Affiliations:
University of Sheffield and National Laboratory for Parallel and Distributed Processing;University of Sheffield;University of Sheffield;University of Sheffield;University of Sheffield
Venue:
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Year:
2005

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Abstract

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.