Skip to main content

Type extensibility of a knowledge representation system with powersets

  • Communications Session 4A Knowledge Representation & Methodologies
  • Conference paper
  • First Online:
Foundations of Intelligent Systems (ISMIS 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1325))

Included in the following conference series:

Abstract

This paper deals with KRSS (knowledge representation systems) close to frame systems including description logic and object-based systems. The main relation that leads to inferences is subsumption which is usually computed over knowledge descriptions that refer to data types. Although subsumption between knowledge terms is well-defined, its implementation on external data types depends upon the host language which is used for the actual implementation of data types. As a consequence, no KRS is able to integrate a new (external) data type such that its values can be safely involved in subsumption and further inferences. This is the problem addressed in this paper. The solution we propose relies on the design of a polymorphic type system connected to both the Krs and the host language. It is designed so that it can extend the KRS with any type implementation available in the host language (standard atomic types, library, package, etc.). Meanwhile, the values of the new type get safely involved in the Krs reasoning processes. The presented type system prevents the incompleteness of subsumption due to its incomplete processing on external data.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. A. Borgida and R.J. Brachman. Protodl: a customizable knowledge base management system. In 1st CIKM, pages 482–490, Baltimore (MA, US), 1992.

    Google Scholar 

  2. A. Borgida, C.L. Isbell, and D.L. McGuinness. Reasoning with black boxes: handling test concepts in Classic. In International Description Logics Workshop, Cambridge (MA, US), November 1996.

    Google Scholar 

  3. R.J. Brachman and J.G. Schmoltze. An overview of the Kl-one knowledge representation language. Cognitive Science, 9:171–216, 1985.

    Google Scholar 

  4. C. Capponi. Design and implementation of a type system for a knowledge representation system. Rapport de Recherche 3096, INRIA Rhône-Alpes, France, January 1997.

    Google Scholar 

  5. C. Capponi, J. Euzenat, and J. Gensel. Objects, types and constraints as classification schemes. In Knowledge Retrieval, Use and Storage for Efficiency, Santa Cruz (CA, US), August 1995.

    Google Scholar 

  6. Y. Crampé. A characterisation of revision in object-based knowledge representation. ISMIS'97, poster Session, Oak Ridge National Laboratory, October 1997.

    Google Scholar 

  7. B.G. Gaines. A class library implementation of a principled open architecture knowledge representation server with plug-in data types. In Ruzena Bajcsy, editor, 13th International Joint Conference on Artificial Intelligence, volume 1, pages 504–509, Chambéry (France), September 1993. Morgan Kaufmann.

    Google Scholar 

  8. J. Gensel. Contraintes et représentation de connaissances par objets. application au modèle Tropes. thèse de 3ème cycle, Université Joseph Fourier, Grenoble, France, October 1995.

    Google Scholar 

  9. ILOG, Gentilly (France). ILOG Talk, version 3.1 (Beta 1), 1994.

    Google Scholar 

  10. R. MacGregor. Inside the Loom classifier. SIGART Bulletin, Special issue on implemented knowledge representation and reasoning systems, 2(3):88–92, June 1991.

    Google Scholar 

  11. F.J. Oles, E.K. Mays, and R.A. Weida. The algebraic essence of K-rep. In International Description Logics Workshop, Cambridge (MA, US), November 1996.

    Google Scholar 

  12. Projet Sherpa, INRIA Rhône-Alpes, Grenoble (France). Tropes, version 1.0 reference manual, June 1995.

    Google Scholar 

  13. P. Valtchev and J. Euzenat. Classification of concepts through products of concepts and abstract data types. In 1st International Conference on Data Analysis and Ordered Structures, pages 131–134, Paris (France), June 1995.

    Google Scholar 

  14. W.A. Woods. Understanding subsumption and taxonomy: a framework for progress. In J.F. Sowa, editor, Principles of Semantic Networks, chapter 1, pages 45–94. Morgan Kaufmann, 1991.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Zbigniew W. Raś Andrzej Skowron

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Capponi, C. (1997). Type extensibility of a knowledge representation system with powersets. In: Raś, Z.W., Skowron, A. (eds) Foundations of Intelligent Systems. ISMIS 1997. Lecture Notes in Computer Science, vol 1325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63614-5_33

Download citation

  • DOI: https://doi.org/10.1007/3-540-63614-5_33

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63614-4

  • Online ISBN: 978-3-540-69612-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics