Mining Domain Specific Texts and Glossaries to Evaluate and Enrich Domain Ontologies

Authors: , Jin-Ping Gwo

Book Title: International Conference of Information and Knowledge Engineering


Abstract: Ontologies have been widely accepted as the most advanced knowledge representation model. They are among the most important building blocks of semantic web, hence, very crucial for the success of semantic web. This paper discusses a fast and efficient method to facilitate the evaluation and enrichment of domain ontologies using a text-mining approach. We exploit domain specific texts and glossaries or dictionaries in order to automatically generate g-groups and f-groups. These groups are sets of concepts/terms which have either taxonomic or non-taxonomic relationships among them. The domain expert ontology engineer reviews these generated groups and uses them to evaluate and enrich the domain ontology. We have developed an extensive and detailed ontology in the field of environmental science using this approach in interaction with domain expert. Empirical results show that our approach can support domain expert ontology engineers in building domain specific ontologies efficiently.

Type: InProceedings

Tags: learning, ontology, semantic web, text mining

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