Skip to main content

Part of the book series: Theory and Decision Library ((TDLD,volume 3))

  • 104 Accesses

Abstract

This Ch. is devoted to central issues arising in any knowledge-based system. Concisely speaking, having already a specified scheme of knowledge representation, we are interested in getting the knowledge concerning the area of interest and, with the aid of the format dictated by the knowledge representation, coding it and indicating a way of effective utilization.

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 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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. P.R. Cohen and E. Feigenbaum, The Handbook of Artificial Intelligence, vol. III, Chapter: Learning and Inductive Inference, Addison Wesley, Reading, Mass., 1986.

    Google Scholar 

  2. T.G. Dietterich and R.S. Michalski, Inductive learning of structural descriptions: Evaluation criteria and comparative review of selected methods, Artificial Intelligence 16 (1981), 257–294.

    Article  MathSciNet  Google Scholar 

  3. A. Di Nola, W. Pedrycz and S. Sessa, Fuzzy relation equations and its applications to knowledge engineering, in: 1st. Suppl. Volume to Systems & Control Encyclopedia (M.G. Singh, Ed.), Pergamon Press Ltd., to appear.

    Google Scholar 

  4. A. Di Nola, W. Pedrycz and S. Sessa, Reduction procedures for rule-based expert systems as a tool for studies of properties of expert’s knowledge, submitted.

    Google Scholar 

  5. R. Kling, A paradigm for reasoning by analogy, Artificial Intelligence 2 (1971), 147178.

    Google Scholar 

  6. W. Pedrycz, Generalization and particularization of production rules in expert systems, in: Cybernetics and Systems ‘86 ( R. Trappl Ed.), D. Reidel Publ. Co., Dordrecht (1986), pp. 783–790

    Google Scholar 

  7. R. Sambuc, Fonctions Ф-floues: application à l’aide en diagnostic in pathologie thyroidienne, Ph.D. Thesis, Marseille, 1975.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 1989 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

di Nola, A., Sessa, S., Pedrycz, W., Sanchez, E. (1989). Construction of Knowledge Base, Its Validation and Optimization. In: Fuzzy Relation Equations and Their Applications to Knowledge Engineering. Theory and Decision Library, vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-1650-5_12

Download citation

  • DOI: https://doi.org/10.1007/978-94-017-1650-5_12

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-4050-3

  • Online ISBN: 978-94-017-1650-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics