Skip to main content

A Fuzzy Description Logic with Automatic Object Membership Measurement

  • Conference paper
Book cover Knowledge Science, Engineering and Management (KSEM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6291))

Abstract

In this paper, we propose a fuzzy description logic named f om -\(\mathcal{DL}\) by combining the classical view in cognitive psychology and fuzzy set theory. A formal mechanism used to determine object memberships automatically in concepts is also proposed, which is lacked in previous work fuzzy description logics. In this mechanism, object membership is based on the defining properties of concept definition and properties in object description. Moreover, while previous works cannot express the qualitative measurements of an object possessing a property, we introduce two kinds of properties named N-property and L-property, which are quantitative measurements and qualitative measurements of an object possessing a property respectively. The subsumption and implication of concepts and properties are also explored in our work. We believe that it is useful to the Semantic Web community for reasoning the fuzzy membership of objects for concepts in fuzzy ontologies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Straccia, U.: Towards a fuzzy description logic for the semantic web. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 167–181. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  2. Stracia, U.: A fuzzy description logic. In: AAAI 1998/IAAI 1998: Proceedings of the Fifteenth National/Tenth Conference on Artificial Intelligence/Innovative Applications of Artificial Intelligence, pp. 594–599 (1998)

    Google Scholar 

  3. Stoilos, G., Stamou, G., Tzouvaras, V., Pan, J.Z., Horrocks, I.: The fuzzy description logic f-\(\cal SHIN\). In: Proc. of the International Workshop on Uncertainty Reasoning for the Semantic Web (2005)

    Google Scholar 

  4. Murphy, G.L.: The big book of concepts. MIT Press, Cambridge (2002)

    Google Scholar 

  5. Galotti, K.M.: Cognitive Psychology In and Out of the Laboratory, 3rd edn. Wadsworth, Belmont (2004)

    Google Scholar 

  6. Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

  7. Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Schneider, P.P. (eds.): The description logic handbook: theory, implementation, and applications. Cambridge University Press, New York (2003)

    MATH  Google Scholar 

  8. Zadeh, L.A.: Fuzzy logic. Computer 21(4), 83–93 (1988)

    Article  Google Scholar 

  9. Klir, G.J., Yuan, B.: Fuzzy sets and fuzzy logic: theory and applications. Prentice hall PTR, Englewood Cliffs (1995)

    MATH  Google Scholar 

  10. Cai, Y., Leung, H.F.: A formal model of fuzzy ontology with property hierarchy and object membership. In: Li, Q., Spaccapietra, S., Yu, E., Olivé, A. (eds.) ER 2008. LNCS, vol. 5231, pp. 69–82. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  11. Smith, E.E., Medin, D.L.: Categories and Concepts. Harvard University Press, Cambridge (1981)

    Google Scholar 

  12. Yager, R.R.: On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Trans. Syst. Man Cybern. 18(1), 183–190 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  13. Yager, R.R.: On mean type aggregation. IEEE Transactions on Systems, Man and Cybernetics 26, 209–221 (1996)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cai, Y., Leung, HF. (2010). A Fuzzy Description Logic with Automatic Object Membership Measurement. In: Bi, Y., Williams, MA. (eds) Knowledge Science, Engineering and Management. KSEM 2010. Lecture Notes in Computer Science(), vol 6291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15280-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15280-1_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15279-5

  • Online ISBN: 978-3-642-15280-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics