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|Abstract=As the amount of available ontologies and their size grow, ontology reuse gains in importance. However, the online available formalized knowledge in many cases need a revision which can lead to a high manual effort. In this paper, we propose an approach to support the revision of ontologies. We show that our method reduces the manual effort measured in number of decisions that have to be made by an ontology engineer by up to 83%.
 
|Abstract=As the amount of available ontologies and their size grow, ontology reuse gains in importance. However, the online available formalized knowledge in many cases need a revision which can lead to a high manual effort. In this paper, we propose an approach to support the revision of ontologies. We show that our method reduces the manual effort measured in number of decisions that have to be made by an ontology engineer by up to 83%.
|Download=ECAI2010.pdf,  
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|Download=ECAI2010.pdf,
 
|Link=http://dx.doi.org/10.3233/978-1-60750-606-5-1097
 
|Link=http://dx.doi.org/10.3233/978-1-60750-606-5-1097
 
|DOI Name=10.3233/978-1-60750-606-5-1097
 
|DOI Name=10.3233/978-1-60750-606-5-1097

Version vom 29. November 2010, 07:37 Uhr


Semi-Automatic Revision of Formalized Knowledge


Semi-Automatic Revision of Formalized Knowledge



Published: 2010 August

Buchtitel: ECAI
Seiten: 1097-1098
Verlag: IOS Press

Nicht-referierte Veröffentlichung

BibTeX

Kurzfassung
As the amount of available ontologies and their size grow, ontology reuse gains in importance. However, the online available formalized knowledge in many cases need a revision which can lead to a high manual effort. In this paper, we propose an approach to support the revision of ontologies. We show that our method reduces the manual effort measured in number of decisions that have to be made by an ontology engineer by up to 83%.

Download: Media:ECAI2010.pdf
Weitere Informationen unter: Link
DOI Link: 10.3233/978-1-60750-606-5-1097

Projekt

NanOn



Forschungsgruppe

Wissensmanagement


Forschungsgebiet

Ontology Engineering