A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
Machine Learning
IJCAR '01 Proceedings of the First International Joint Conference on Automated Reasoning
The Description Logic Handbook
The Description Logic Handbook
Pellet: A practical OWL-DL reasoner
Web Semantics: Science, Services and Agents on the World Wide Web
Debugging Incoherent Terminologies
Journal of Automated Reasoning
QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
A catalogue of OWL ontology antipatterns
Proceedings of the fifth international conference on Knowledge capture
Finding all justifications of OWL DL entailments
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
A general diagnosis method for ontologies
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Repairing unsatisfiable concepts in OWL ontologies
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Using provenance to debug changing ontologies
Web Semantics: Science, Services and Agents on the World Wide Web
Interactive ontology debugging: Two query strategies for efficient fault localization
Web Semantics: Science, Services and Agents on the World Wide Web
Hi-index | 0.01 |
Debugging is an important prerequisite for the wide-spread application of ontologies, especially in areas that rely upon everyday users to create and maintain knowledge bases, such as the Semantic Web. Most recent approaches use diagnosis methods to identify sources of inconsistency. However, in most debugging cases these methods return many alternative diagnoses, thus placing the burden of fault localization on the user. This paper demonstrates how the target diagnosis can be identified by performing a sequence of observations, that is, by querying an oracle about entailments of the target ontology. We exploit probabilities of typical user errors to formulate information theoretic concepts for query selection. Our evaluation showed that the suggested method reduces the number of required observations compared to myopic strategies.