The application of automated reasoning approaches to Description Logic (DL) ontologies may produce certain consequences that either are deemed to be wrong or should be hidden for privacy reasons. The question is then how to repair the ontology such that the unwanted consequences can no longer be deduced. An optimal repair is one where the least amount of other consequences is removed. Most of the previous approaches to ontology repair are of a syntactic nature in that they remove or weaken the axioms explicitly present in the ontology, and thus cannot achieve semantic optimality. In previous work, we have addressed the problem of computing optimal repairs of (quantified) ABoxes, where the unwanted consequences are described by concept asser...
As semantically-enabled applications require high-quality ontologies, developing and maintaining ont...
Unsatisfiable concepts are a major cause for inconsistencies in Description Logics knowledge bases. ...
The development and maintenance of large and complex on-tologies are often time-consuming and error-...
The application of automated reasoning approaches to Description Logic (DL) ontologies may produce c...
Errors in Description Logic (DL) ontologies are often detected when a reasoner computes unwanted con...
Reasoners can be used to derive implicit consequences from an ontology. Sometimes unwanted consequen...
Ontologies based on Description Logic (DL) represent general background knowledge in a terminology (...
Ontologies based on Description Logics may contain errors, which are usually detected when reasoning...
Errors in knowledge bases (KBs) written in a Description Logic (DL) are usually detected when reason...
We review our recent work on how to compute optimal repairs, optimal compliant anonymizations, and o...
Ontology engineering is a hard and error-prone task, in which small changes may lead to er...
The classical approach for repairing a Description Logic ontology O in the sense of removing an unwa...
Ontology engineering is a hard and error-prone task, in which small changes may lead to errors, or e...
ABox abduction plays an important role in reasoning over description logic (DL) ontologies. However,...
Abstract. In recent years, there has been significant progress in devel-oping tools for debugging an...
As semantically-enabled applications require high-quality ontologies, developing and maintaining ont...
Unsatisfiable concepts are a major cause for inconsistencies in Description Logics knowledge bases. ...
The development and maintenance of large and complex on-tologies are often time-consuming and error-...
The application of automated reasoning approaches to Description Logic (DL) ontologies may produce c...
Errors in Description Logic (DL) ontologies are often detected when a reasoner computes unwanted con...
Reasoners can be used to derive implicit consequences from an ontology. Sometimes unwanted consequen...
Ontologies based on Description Logic (DL) represent general background knowledge in a terminology (...
Ontologies based on Description Logics may contain errors, which are usually detected when reasoning...
Errors in knowledge bases (KBs) written in a Description Logic (DL) are usually detected when reason...
We review our recent work on how to compute optimal repairs, optimal compliant anonymizations, and o...
Ontology engineering is a hard and error-prone task, in which small changes may lead to er...
The classical approach for repairing a Description Logic ontology O in the sense of removing an unwa...
Ontology engineering is a hard and error-prone task, in which small changes may lead to errors, or e...
ABox abduction plays an important role in reasoning over description logic (DL) ontologies. However,...
Abstract. In recent years, there has been significant progress in devel-oping tools for debugging an...
As semantically-enabled applications require high-quality ontologies, developing and maintaining ont...
Unsatisfiable concepts are a major cause for inconsistencies in Description Logics knowledge bases. ...
The development and maintenance of large and complex on-tologies are often time-consuming and error-...