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

Coherence, Similarity, and Concept Generalisation

We address the problem of analysing the joint coherence of a number of concepts with respect to a background ontology. To address this problem, we explore the applicability of Paul Thagard's computational theory of coherence, in combination with semantic similarity between concepts based on a generalisation operator. In particular, given the input concepts, our approach computes maximally coherent subsets of these concepts following Thagard's partitioning approach, whilst returning a number of possible generalisations of these concepts as justifi- cation of why these concepts cohere.Peer Reviewe