Predicting the understandability of OWL inferences

Nguyen, Tu Anh T.; Power, Richard; Piwek, Paul and Williams, Sandra (2013). Predicting the understandability of OWL inferences. In: Extended Semantic Web Conference 2013 (ESWC 2013) - Research Track, 26 May to 30 May 2013, Montpellier, France, pp. 109–123.

DOI: https://doi.org/10.1007/978-3-642-38288-8_8

Abstract

In this paper, we describe a method for predicting the understandability level of inferences with OWL. Specifically, we present a 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.

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About

• Item ORO ID
• 36692
• Item Type
• Conference or Workshop Item
• Extra Information
• Paper appears in "The Semantic Web: Semantics and Big Data, Lecture Notes in Computer Science Volume 7882, 2013, pp 109-123"
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM)
  Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
• Research Group
• Centre for Research in Computing (CRC)
• Copyright Holders
• © 2013 Springer-Verlag
• Related URLs
• • http://2013.eswc-conferences.org/program...(Other)
• Depositing User
• Tu Nguyen