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

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dc.contributor.authorParekh, Viral
dc.contributor.authorGwo, Jack
dc.contributor.authorFinin, Tim
dc.date.accessioned2018-12-18T16:42:12Z
dc.date.available2018-12-18T16:42:12Z
dc.date.issued2004-06-21
dc.descriptionInternational Conference of Information and Knowledge Engineeringen_US
dc.description.abstractOntologies 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.en_US
dc.description.urihttps://ebiquity.umbc.edu/paper/html/id/171/Mining-Domain-Specific-Texts-and-Glossaries-to-Evaluate-and-Enrich-Domain-Ontologiesen_US
dc.format.extent7 pagesen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/M23X83Q4H
dc.identifier.urihttp://hdl.handle.net/11603/12296
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectontology enrichmenten_US
dc.subjecttext miningen_US
dc.subjectclusteringen_US
dc.subjectfeature groupsen_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleMining Domain Specific Texts and Glossaries to Evaluate and Enrich Domain Ontologiesen_US
dc.typeTexten_US

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