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Use of Models in the Interpretation of Verbal Data

  • Joost Breuker
  • Bob Wielinga

Abstract

The experience of building expert systems for a decade has revealed a number of problems and bottlenecks at each stage of the life cycle. Although the evidence is not abundant, because the number of fully operational expert systems is small with respect to the number of systems that have been developed, it appears that ad hoc or post hoc solutions for problems in early stages can create new and even bigger problems at later stages (McDermott, 1983, 1984): Problems propagate. The fact that few systems ever reach operational maturity is probably indicative of the fact that the art of knowledge engineering is not well established yet. The major problems are listed in the reverse order of their life cycle stages, because problems at later stages are more easily identified.

Keywords

Expert System Knowledge Acquisition Knowledge Source Knowledge Engineer Interpretation Model 
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.

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Copyright information

© Plenum Press, New York 1987

Authors and Affiliations

  • Joost Breuker
    • 1
  • Bob Wielinga
    • 1
  1. 1.Department of Social Science InformaticsUniversity of AmsterdamAmsterdamThe Netherlands

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