Guiding interactive ontology repair through prolific and relevant axioms

Knowledge engineering is an error-prone task and the need for automated tools to help correct existing errors has been long recognised. While many ontology repair methods have been proposed, most ignore a fundamental issue: only a domain expert can state whether an ontology reflects the domain knowledge or not. In this paper, we consider an interactive ontology repair procedure where a domain expert guides the system by signalling axioms that are identified as erroneous from sets of suspicious axioms. To avoid overwhelming the human expert with the number and complexity of information requests, we propose methods to reduce the class of potentially suspicious axioms: first, the expert may signal a class of consequences they desire to preserve in the corrected ontology; second, we introduce a new notion of prolificacy to understand the impact axioms have in the derivation of consequences.