Philipp Fleiss

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Debugging of ontologies is an important prerequisite for their wide-spread application, especially in areas that rely upon everyday users to create and maintain knowledge bases, as in the case of the Semantic Web. Recent approaches use diagnosis methods to identify causes of inconsistent or incoherent ontologies. However, in most debugging scenarios these(More)
Interactive ontology debugging incorporates a user who answers queries about entailments of their intended ontology. In order to minimize the amount of user interaction in a debugging session, a user must choose an appropriate query selection strategy. However, the choice of an unsuitable strategy may result in tremendous overhead in terms of time and cost.(More)
Sequential ontology debugging is aimed at the efficient discrimination between diagnoses, i.e. sets of axioms which must be altered or deleted from the ontology to restore consistency. By querying additional information the number of possible diagnoses can be gradually reduced. The selection of the best queries is crucial for minimizing diagnosis costs. If(More)
Sequential diagnosis methods compute a series of queries for discriminating between diagnoses. Queries are answered by some oracle such that eventually the set of faults is identified. The computation of queries is based on the generation of a set of most probable diagnoses. However, in diagnosis problem instances where the number of minimal diagnoses and(More)
Efficient ontology debugging is a cornerstone for many activities in the context of the Semantic Web, especially when automatic tools produce (parts of) ontologies such as in the field of ontology matching. The best currently known interactive debugging systems rely upon meta information in terms of fault probabilities, which can speed up the debugging(More)
Modern ontology debugging methods allow efficient identification and localization of faulty axioms in an ontology. However, in many use cases such as ontology alignment the ontologies might include many conflict sets, i.e. sets of axioms preserving the faults, thus making ontology diagnosis infeasible. In this paper we present a debugging approach based on(More)
Sequential diagnosis methods compute a series of queries for discriminating between diagnoses. Queries are answered by probing such that eventually the set of faults is identified. The computation of queries is based on the generation of a set of most probable diagnoses. However, in diagnosis problem instances where the number of minimal diagnoses and their(More)
Modern ontology debugging methods allow efficient identification and localization of faulty axioms defined by a user while developing an ontology. The ontology development process in this case is characterized by rather frequent and regular calls to a reasoner resulting in an early user awareness of modeling errors. In such a scenario an ontology usually(More)
Modern ontology debugging methods allow efficient identification and localization of faulty axioms defined by a user while developing an ontology. However, in many use cases such as ontology alignment the ontologies might include many conflict sets, i.e. sets of axioms preserving the faults, thus making the ontology diagnosis infeasible. In this paper we(More)