Knowledge base organization in expert systems

  • S. Frediani
  • L. Saitta
Section II Approaches To Uncertainty D) General Issues
Part of the Lecture Notes in Computer Science book series (LNCS, volume 286)


This paper describes a method for performing knowledge base (re)organization in Expert Systems oriented to classification, interpretation and diagnosis problems. The methodology can be applied either to the input descriptions of a set of samples, giving thus a preliminary characterization of groups of samples, or to a set of intermediate level descriptions, supplied by a human expert or previously automatically learned. An example of application is also given.


Expert System Production Rule Human Expert Knowledge Organization Certainty Factor 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    -F. Bergadano, A. Giordana and L. Saitta: "Approximate Reasoning in Knowledge Acquisition", in "Fuzzy Logic in Knowledge Engineering", C.Negoita and H.Prade (Ed.s), (1985), 127–148.Google Scholar
  2. [2]
    -Y. Cheng and K.S. Fu: "Conceptual Clustering in Knowledge Organization", IEEE Trans. on Pattern Analysis and Machine Intelligence, PAMI-7, 592–598, (1985).Google Scholar
  3. [3]
    -L.M. Fu and B. Buchanan: "Learning Intermediate Concepts in constructing a Hierarchical Knowledge Base", Proc. IJCAI-85 (Los Angeles, CA, 1985), pag. 659–666.Google Scholar
  4. [4]
    -F. Hayes-Roth and J. McDermott: "An Interference Matching Technique for Inducing Abstractions", Comm. ACM, 21, 401–411, (1978).Google Scholar
  5. [5]
    -T. Mitchell: "Generalization as Search", Artificial Intelligence, 18, 203–226, (1982).Google Scholar
  6. [6]
    -R.S. Michalski: "Pattern Recognition as Rule-Guided Inductive Inference", IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-2, 349–361, (1980).Google Scholar
  7. [7]
    -A. Heeffer: "Validating Concepts from Automated Acquisition Systems", Proc. IJCAI-85 (Los Angeles, CA, 1985), pag. 613–615.Google Scholar
  8. [8]
    -B. Arbab and D. Michie: "Generating Rules from Examples", Proc. IJCAI-85 (Los Angeles, CA, 1985) pag. 631–633.Google Scholar
  9. [9]
    -B.G. Buchanan and T. Mitchell: "Model-directed Learning of Production Rules", in ‘Pattern-Directed Inference Systems', D.A. Waterman and F. Hayes-Roth (Ed.s), Academic Press, (1978), pag. 297–312.Google Scholar
  10. [10]
    -S.A. Vere: "Multilevel Counterfactuals for Generalizations of Relational Concepts and Productions", Artificial Intelligence, 14, 139–164, (1980).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1987

Authors and Affiliations

  • S. Frediani
    • 1
  • L. Saitta
    • 2
  1. 1.C.E.N.S. - Dipartimento di Automatica e InformaticaPolitecnico di TorinoTorinoItaly
  2. 2.Dipartimento di InformaticaUniversita` di TorinoTorinoItaly

Personalised recommendations