Abstract
In this paper we describe a system aimed at providing software support for the process of knowledge acquisition. Such support comprises a workbench incorporating a number of knowledge acquisition tools; knowledge elicitation techniques such as sorting and rating methods, together with machine learning techniques. The paper discusses the various problems raised by this work. These include; defining an adequate view of the general acquisition process, developing an appropriate implementation architecture, directing knowledge acquisition via knowledge level models and producing a sufficiently powerful representation language to integrate the results of acquisition. Finally we describe the limitations of our current system and future developments in our work.
We would like to thank Nigel Major for his help in implementing aspects of ProtoKEW, to Peter Terpstra of the University of Amsterdam and GEC Marconi Research Centre who made available software for inclusion in ProtoKEW. Thanks also to Anjo Anjewierden who commented on an earlier version of this paper. This research was carried out, in part, under the auspices of ESPRIT P2576 ACKnowledge. The ACKnowledge consortium comprises: Cap Sesa Innovation, Marconi Command and Control Systems, GEC-Marconi Research Centre, Telefonica, Computas Expert Systems, Veritas Research, the University of Amsterdam, Sintef, and the University of Nottingham
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© 1991 Springer-Verlag London Limited
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Reichgelt, H., Shadbolt, N. (1991). Knowledgeable knowledge acquisition. In: Steels, L., Smith, B. (eds) AISB91. Springer, London. https://doi.org/10.1007/978-1-4471-1852-7_15
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DOI: https://doi.org/10.1007/978-1-4471-1852-7_15
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