Predicting the understandability of OWL inferences

Abstract

In this paper, we describe a method for predicting the understandability level of inferences with OWL. Specifically, we present a probabilistic model for measuring the understandability of a multiple-step inference based on the measurement of the understandability of individual inference steps. We also present an evaluation study which confirms that our model works relatively well for two-step inferences with OWL. This model has been applied in our research on generating accessible explanations for an entailment of OWL ontologies, to determine the most understandable inference among alternatives, from which the final explanation is generated. © 2013 Springer-Verlag Berlin Heidelberg.