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| − | |Abstract=Quality control is an essential task within ontology development projects especially when the knowledge formalization is partially automatized. In this paper, we propose a reasoning-based, interactive approach to support the revision of formalized knowledge. In this approach, the evaluation decisions taken by a human expert are propagated in order to automatically evaluate axioms and thereby reduce the number of axioms that have to be manually evaluated. Additionally, we propose a ranking technique to further increase the effectiveness of ontology revision and provide an evaluation in terms of effort reduction | + | |Abstract=Quality control is an essential task within ontology development projects especially when the knowledge formalization is partially automatized. In this paper, we propose a reasoning-based, interactive approach to support the revision of formalized knowledge. In this approach, the evaluation decisions taken by a human expert are propagated in order to automatically evaluate axioms and thereby reduce the number of axioms that have to be manually evaluated. Additionally, we propose a ranking technique to further increase the effectiveness of ontology revision and provide an evaluation in terms of effort reduction with encouraging results. |
| − | |Download= | + | |Download=ECAI-821-270810.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 27. Oktober 2010, 07:17 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
Quality control is an essential task within ontology development projects especially when the knowledge formalization is partially automatized. In this paper, we propose a reasoning-based, interactive approach to support the revision of formalized knowledge. In this approach, the evaluation decisions taken by a human expert are propagated in order to automatically evaluate axioms and thereby reduce the number of axioms that have to be manually evaluated. Additionally, we propose a ranking technique to further increase the effectiveness of ontology revision and provide an evaluation in terms of effort reduction with encouraging results.
Download: Media:ECAI-821-270810.pdf
Weitere Informationen unter: Link
DOI Link: 10.3233/978-1-60750-606-5-1097