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Domain-driven knowledge modelling: Mediating & intermediate representations for knowledge acquisition

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 599)

Abstract

Knowledge modelling, despite the existence of numerous techniques and tools, still remain an ad hoc process which is still more of an art than a science. This is due to the fact that there is as yet no systematic or formal theory for it. Naturally, it is a central goal of the Knowledge Acquisition community to make this process more principled. This paper presents a theoretical framework which is an extension of some of the current thinking about knowledge modelling, with hopefully some clarifications. It draws heavily from the knowledge acquisition literature; its key contribution is a novel combination of known techniques into some (hopefully) coherent framework, rather than a radical new philosophy for knowledge modelling. This framework has been used for several projects we have carried out for industrial partners; it is also the basis of a hybrid tool we intend to develop.

Keywords

Knowledge Acquisition Knowledge Modelling Knowledge Engineer Intermediate Representation Knowledge Type 
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

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of KeeleKeeleUK
  2. 2.Department of Computer ScienceUniversity of LiverpoolLiverpoolUK

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