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Conceptual models for automatic generation of knowledge-acquisition tools

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Current Developments in Knowledge Acquisition — EKAW '92 (EKAW 1992)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 599))

Abstract

Interactive knowledge-acquisition (KA) programs allow users to enter relevant domain knowledge according to a model predefined by the tool developers. KA tools are designed to provide conceptual models of the knowledge to their users. Many different classes of models are possible, resulting in different categories of tools. Whenever it is possible to describe KA tools according to explicit conceptual models, it is also possible to edit the models and to instantiate new KA tools automatically for specialized purposes. Several meta-tools that address this task have been implemented. Meta-tools provide developers of domain-specific KA tools with generic design models, or meta-views, of the emerging KA tools. The same KA tool can be specified according to several alternative meta-views.

On leave from the Department of Computer and Information Science, Linköping University, S-581 83 Linköping, Sweden

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Authors and Affiliations

  1. Medical Computer Science Group Knowledge Systems Laboratory, Stanford University School of Medicine, 94305-5470, Stanford, CA, USA

    Henrik Eriksson & Mark A. Musen

Authors
  1. Henrik Eriksson
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  2. Mark A. Musen
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Editor information

Thomas Wetter Klaus-Dieter Althoff John Boose Brian R. Gaines Marc Linster Franz Schmalhofer

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© 1992 Springer-Verlag Berlin Heidelberg

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Eriksson, H., Musen, M.A. (1992). Conceptual models for automatic generation of knowledge-acquisition tools. In: Wetter, T., Althoff, KD., Boose, J., Gaines, B.R., Linster, M., Schmalhofer, F. (eds) Current Developments in Knowledge Acquisition — EKAW '92. EKAW 1992. Lecture Notes in Computer Science, vol 599. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55546-3_32

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  • DOI: https://doi.org/10.1007/3-540-55546-3_32

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-55546-9

  • Online ISBN: 978-3-540-47203-2

  • eBook Packages: Springer Book Archive

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