Advertisement

Constructive Justification Extraction for OWL Ontologies

  • Yuxin Ye
  • Ling Zhang
  • Dantong Ouyang
  • Mengyu Gao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11062)

Abstract

Extracting justifications for the OWL (Ontology Web Language) ontologies is applicable to a wide range of practical applications. In this paper, we introduce a kind of methods of justifications extraction in a constructive way, which are different from traditional methods in a destructive way. In the process of constructive extraction, the justification will be created by adding the detected critical axioms iteratively. First of all, we state a naive constructive justifications extraction method, and analyze the number of calls to the ontology reasoner by this algorithm which is \(\varvec{\mathcal {O}}(m*k)\). In the following, we devise an advanced constructive justification algorithm that takes only \(\varvec{\varTheta }(m)\) calls to the ontology reasoner. The key techniques to ensure the success of such algorithm are axiom-selector and AtMost 1 constraint to be introduced. The experimental results show that our advanced constructive justification algorithm achieves significant performance compared to the traditional methods.

Keywords

Semantic web Ontology reasoning Justification extraction Black-box technique 

Notes

Acknowledgments

Research presented in this paper was partially supported by National Science Foundation of China (no. 61672261, 61502199). It’s also funded by China Scholarship Council (no. 201506175028) for the first author of this paper. We also would like to be grateful to the partners in the laboratory who have given our generous support and helpful advice for this research.

References

  1. 1.
    Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, Cambridge (2010)MATHGoogle Scholar
  2. 2.
    Baader, F., Suntisrivaraporn, B.: Debugging SNOMED CT using axiom pinpointing in the description logic EL+. In: Proceedings of the Third International Conference on Knowledge Representation in Medicine, 31 May–2 June 2008, Phoenix, Arizona, USA (2008). http://ceur-ws.org/Vol-410/Paper01.pdf
  3. 3.
    Desrosiers, C., Galinier, P., Hertz, A., Paroz, S.: Using heuristics to find minimal unsatisfiable subformulas in satisfiability problems. J. Comb. Optim. 18(2), 124–150 (2009).  https://doi.org/10.1007/s10878-008-9142-4MathSciNetCrossRefMATHGoogle Scholar
  4. 4.
    Grégoire, É., Mazure, B., Piette, C.: On approaches to explaining infeasibility of sets of boolean clauses. In: 20th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2008), 3–5 November 2008, Dayton, Ohio, USA, vol. 1, pp. 74–83 (2008).  https://doi.org/10.1109/ICTAI.2008.39
  5. 5.
    Jannach, D., Schmitz, T., Shchekotykhin, K.M.: Parallel model-based diagnosis on multi-core computers. J. Artif. Intell. Res. 55, 835–887 (2016).  https://doi.org/10.1613/jair.5001MathSciNetCrossRefMATHGoogle Scholar
  6. 6.
    Ji, Q., Gao, Z., Huang, Z., Zhu, M.: Measuring effectiveness of ontology debugging systems. Knowl.-Based Syst. 71, 169–186 (2014).  https://doi.org/10.1016/j.knosys.2014.07.023CrossRefGoogle Scholar
  7. 7.
    Kalyanpur, A.: Debugging and repair of OWL ontologies. Ph.D. thesis, University of Maryland, College Park, MD, USA (2006). http://hdl.handle.net/1903/3820
  8. 8.
    Kalyanpur, A., Parsia, B., Horridge, M., Sirin, E.: Finding all justifications of OWL DL entailments. In: Aberer, K., et al. (eds.) ASWC/ISWC -2007. LNCS, vol. 4825, pp. 267–280. Springer, Heidelberg (2007).  https://doi.org/10.1007/978-3-540-76298-0_20CrossRefGoogle Scholar
  9. 9.
    Schlobach, S., Cornet, R.: Non-standard reasoning services for the debugging of description logic terminologies. In: Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03, 9–15 August 2003, Acapulco, Mexico, pp. 355–362 (2003)Google Scholar
  10. 10.
    Schlobach, S., Huang, Z., Cornet, R., van Harmelen, F.: Debugging incoherent terminologies. J. Autom. Reason. 39(3), 317–349 (2007).  https://doi.org/10.1007/s10817-007-9076-zMathSciNetCrossRefMATHGoogle Scholar
  11. 11.
    Silva, J.P.M.: Minimal unsatisfiability: models, algorithms and applications (invited paper). In: 40th IEEE International Symposium on Multiple-Valued Logic, ISMVL 2010, 26–28 May 2010, Barcelona, Spain, pp. 9–14 (2010).  https://doi.org/10.1109/ISMVL.2010.11
  12. 12.
    Sinz, C.: Towards an optimal CNF encoding of boolean cardinality constraints. In: van Beek, P. (ed.) CP 2005. LNCS, vol. 3709, pp. 827–831. Springer, Heidelberg (2005).  https://doi.org/10.1007/11564751_73CrossRefMATHGoogle Scholar
  13. 13.
    Suntisrivaraporn, B., Baader, F., Schulz, S., Spackman, K.: Replacing SEP-triplets in SNOMED CT using tractable description logic operators. In: Bellazzi, R., Abu-Hanna, A., Hunter, J. (eds.) AIME 2007. LNCS (LNAI), vol. 4594, pp. 287–291. Springer, Heidelberg (2007).  https://doi.org/10.1007/978-3-540-73599-1_38CrossRefGoogle Scholar
  14. 14.
    Ye, Y., Cui, X., Ouyang, D.: Extracting a justification for owl ontologies by critical axioms. Front. Comput. Sci. (Accepted)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Yuxin Ye
    • 1
    • 2
    • 3
  • Ling Zhang
    • 1
  • Dantong Ouyang
    • 1
    • 2
    • 3
  • Mengyu Gao
    • 3
  1. 1.College of SoftwareJilin UniversityChangchunChina
  2. 2.Key Laboratory of Symbolic Computing and Knowledge Engineering, Ministry of EducationJilin UniversityChangchunChina
  3. 3.College of Computer Science and TechnologyJilin UniversityChangchunChina

Personalised recommendations