491 research outputs found
Get my pizza right: Repairing missing is-a relations in ALC ontologies (extended version)
With the increased use of ontologies in semantically-enabled applications,
the issue of debugging defects in ontologies has become increasingly important.
These defects can lead to wrong or incomplete results for the applications.
Debugging consists of the phases of detection and repairing. In this paper we
focus on the repairing phase of a particular kind of defects, i.e. the missing
relations in the is-a hierarchy. Previous work has dealt with the case of
taxonomies. In this work we extend the scope to deal with ALC ontologies that
can be represented using acyclic terminologies. We present algorithms and
discuss a system
Repairing Ontologies via Axiom Weakening.
Ontology engineering is a hard and error-prone task, in which
small changes may lead to errors, or even produce an inconsistent
ontology. As ontologies grow in size, the need for automated
methods for repairing inconsistencies while preserving
as much of the original knowledge as possible increases.
Most previous approaches to this task are based on removing
a few axioms from the ontology to regain consistency.
We propose a new method based on weakening these axioms
to make them less restrictive, employing the use of refinement
operators. We introduce the theoretical framework for
weakening DL ontologies, propose algorithms to repair ontologies
based on the framework, and provide an analysis of
the computational complexity. Through an empirical analysis
made over real-life ontologies, we show that our approach
preserves significantly more of the original knowledge of the
ontology than removing axioms
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Justification Patterns for OWL DL Ontologies
For debugging OWL-DL ontologies, natural language explanations of inconsistencies and undesirable entailments are of great help. From such explanations, ontology developers can learn why an ontology gives rise to specific entailments. Unfortunately, commonly used tableaux-based reasoning services do not provide a basis for such explanations, since they rely on a refutation proof strategy and normalising transformations that are difficult for human ontology editors to understand. For this reason, we investigate the use of automatically generated justifications for entailments (i.e., minimal sets of axioms from the ontology that cause entailments to hold). We show that such justifications fall into a manageable number of patterns, which can be used as a basis for generating natural language explanations by associating each justification pattern with a rhetorical pattern in natural language
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