Concept refinement operators have been introduced to describe and compute generalisations and specialisations of concepts, with, amongst others, applications in concept learning and ontology repair through axiom weakening. We here provide a probabilistic proof of almost-certain termination for iterated refinements, thus for an axiom weakening procedure for the fine-grained repair of ALC ontologies. We determine the computational complexity of refinement membership, and discuss performance aspects of a prototypical implementation, verifying that almost-certain termination means actual termination in practice.

Almost Certain Termination for ALC Weakening

Confalonieri R.;
2022

Abstract

Concept refinement operators have been introduced to describe and compute generalisations and specialisations of concepts, with, amongst others, applications in concept learning and ontology repair through axiom weakening. We here provide a probabilistic proof of almost-certain termination for iterated refinements, thus for an axiom weakening procedure for the fine-grained repair of ALC ontologies. We determine the computational complexity of refinement membership, and discuss performance aspects of a prototypical implementation, verifying that almost-certain termination means actual termination in practice.
2022
EPIA Conference on Artificial Intelligence EPIA 2022: Progress in Artificial Intelligence
978-3-031-16473-6
978-3-031-16474-3
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3471611
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