Predicting the Understandability of OWL Inferences

  • Tu Anh T. Nguyen
  • Richard Power
  • Paul Piwek
  • Sandra Williams
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7882)


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.


Correct Answer Description Logic Proof Tree Deduction Rule Inference Step 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Tu Anh T. Nguyen
    • 1
  • Richard Power
    • 1
  • Paul Piwek
    • 1
  • Sandra Williams
    • 1
  1. 1.Department of ComputingThe Open UniversityMilton KeynesUK

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