Advertisement

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)

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.

Keywords

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.

References

  1. 1.
    OWL 2 Web Ontology Language Document Overview, 2nd edn., http://www.w3.org/TR/owl2-overview/ (last accessed: February 1, 2013)
  2. 2.
    Baader, F., Peñaloza, R., Suntisrivaraporn, B.: Pinpointing in the Description Logic \(\mathcal{EL}^+\). In: Hertzberg, J., Beetz, M., Englert, R. (eds.) KI 2007. LNCS (LNAI), vol. 4667, pp. 52–67. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  3. 3.
    Horridge, M., Bail, S., Parsia, B., Sattler, U.: The Cognitive Complexity of OWL Justifications. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011, Part I. LNCS, vol. 7031, pp. 241–256. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  4. 4.
    Horridge, M., Drummond, N., Goodwin, J., Rector, A., Stevens, R., Wang, H.: The Manchester OWL Syntax. In: International Workshop on OWL: Experiences and Directions (OWLED 2006) (2006)Google Scholar
  5. 5.
    Horridge, M., Parsia, B., Sattler, U.: Lemmas for Justifications in OWL. In: International Workshop on Description Logics (DL 2009) (2009)Google Scholar
  6. 6.
    Ji, Q., Qi, G., Haase, P.: A Relevance-Directed Algorithm for Finding Justifications of DL Entailments. In: Gómez-Pérez, A., Yu, Y., Ding, Y. (eds.) ASWC 2009. LNCS, vol. 5926, pp. 306–320. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  7. 7.
    Kalyanpur, A., Parsia, B., Horridge, M., Sirin, E.: Finding All Justifications of OWL DL Entailments. In: Aberer, K., et al. (eds.) ISWC/ASWC 2007. LNCS, vol. 4825, pp. 267–280. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. 8.
    Kalyanpur, A., Parsia, B., Sirin, E., Hendler, J.: Debugging Unsatisfiable Classes in OWL Ontologies. Journal of Web Semantics 3(4), 268–293 (2005)CrossRefGoogle Scholar
  9. 9.
    Lam, J.S.C., Sleeman, D., Pan, J.Z., Vasconcelos, W.W.: A Fine-Grained Approach to Resolving Unsatisfiable Ontologies. In: Spaccapietra, S. (ed.) Journal on Data Semantics X. LNCS, vol. 4900, pp. 62–95. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  10. 10.
    Motik, B., Shearer, R., Horrocks, I.: A Hypertableau Calculus for \(\mathcal{SHIQ}\). In: International Workshop on Description Logics (DL 2007), pp. 419–426 (2007)Google Scholar
  11. 11.
    Newstead, S.E., Bradon, P., Handley, S.J., Dennis, I., Evans, J.S.B.T.: Predicting the difficulty of complex logical reasoning problems. Thinking & Reasoning 12(1), 62–90 (2006)CrossRefGoogle Scholar
  12. 12.
    Nguyen, T.A.T., Power, R., Piwek, P., Williams, S.: Measuring the Understandability of Deduction Rules for OWL. In: International Workshop on Debugging Ontologies and Ontology Mappings (WoDOOM 2012) (2012)Google Scholar
  13. 13.
    Schlobach, S., Cornet, R.: Non-standard Reasoning Services for the Debugging of Description Logic Terminologies. In: International Joint Conference on Artificial Intelligence (IJCAI 2003), pp. 355–360 (2003)Google Scholar
  14. 14.
    Sirin, E., Parsia, B., Grau, B.C., Kalyanpur, A., Katz, Y.: Pellet: A Practical OWL-DL Reasoner. Journal of Web Semantics 5, 51–53 (2007)CrossRefGoogle Scholar
  15. 15.
    Tsarkov, D., Horrocks, I.: FaCT++ Description Logic Reasoner: System Description. In: Furbach, U., Shankar, N. (eds.) IJCAR 2006. LNCS (LNAI), vol. 4130, pp. 292–297. Springer, Heidelberg (2006)CrossRefGoogle Scholar

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

Personalised recommendations