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Knowledge modelling for a generic refinement framework.

Boswell, R.; Craw, S.

Authors

R. Boswell



Abstract

Refinement tools assist with debugging the knowledge-based system (KBS), thus easing the well-known knowledge acquisition bottleneck, and the more recently recognised maintenance overhead. The existing refinement tools were developed for specific rule-based KBS environments, and have usually been applied to artificial or academic applications. Hence, there is a need for tools which are applicable to industrial applications. However, it would be wasteful to develop separate refinement tools for individual shells; instead, the KrustWorks project is developing reusable components applicable to a variety of KBS environments. This paper develops a knowledge representation that embodies a KBS's rulebase and its reasoning, and permits the implementation of core refinement procedures, which are generally applicable and can ignore KBS-specific details. Such a representation is an essential stage in the construction of a generic automated knowledge refinement framework, such as KrustWorks. Experience from applying this approach to Clips, PowerModel and Pfes KBSs indicates its feasibility for a wider variety of industrial KBSs.

Citation

BOSWELL, R. and CRAW, S. 1999. Knowledge modelling for a generic refinement framework. Knowledge-based systems [online], 12(5-6), pages 317-325. Available from: https://doi.org/10.1016/S0950-7051(99)00018-0

Journal Article Type Article
Acceptance Date Oct 31, 1999
Online Publication Date Oct 31, 1999
Publication Date Oct 31, 1999
Deposit Date Mar 22, 2007
Publicly Available Date Mar 22, 2007
Journal Knowledge-based systems
Print ISSN 0950-7051
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 12
Issue 5-6
Pages 317-325
DOI https://doi.org/10.1016/S0950-7051%2899%2900018-0
Keywords Knowledge refinement; Knowledge representation; Knowledge acquisition
Public URL http://hdl.handle.net/10059/58

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