RIO: Minimizing user interaction in ontology debugging

Abstract

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. We present a learning method for query selection which unites the advantages of existing approaches while overcoming their flaws. Our tests show the utility of our approach when applied to a large set of real-world ontologies, its scalability and adequate reaction time allowing for continuous interactivity.