A Survey of Exploiting WordNet in Ontology Matching

Nowadays, many ontologies are used in industry, public adminstration and academia. Although these ontologies are developed for various purposes and domains, they often contain overlapping information. To build a collaborative semantic web, which allows data to be shared and reused across application...

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Bibliographic Details
Published inArtificial Intelligence in Theory and Practice II pp. 341 - 350
Main Authors Lin, Feiyu, Sandkuhl, Kurt
Format Book Chapter
LanguageEnglish
Published Boston, MA Springer US 2008
SeriesIFIP – The International Federation for Information Processing
Subjects
Entity Class
Ontology Match
Semantic Similarity
Semantic Similarity Measure
String Similarity
Online AccessGet full text
ISBN0387096949
9780387096940
ISSN1868-4238
DOI10.1007/978-0-387-09695-7_33

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Summary:Nowadays, many ontologies are used in industry, public adminstration and academia. Although these ontologies are developed for various purposes and domains, they often contain overlapping information. To build a collaborative semantic web, which allows data to be shared and reused across applications, enterprises, and community boundaries, it is necessary to find ways to compare, match and integrate various ontologies. Different strategies (e.g., string similarity, synonyms, structure similarity and based on instances) for determining similarity between entities are used in current ontology matching systems. Synonyms can help to solve the problem of using different terms in the ontologies for the same concept. The WordNet thesauri can support improving similarity measures. This paper provides an overview of how to apply WordNet in the ontology matching research area.
ISBN:0387096949
9780387096940
ISSN:1868-4238
DOI:10.1007/978-0-387-09695-7_33