Knowledge modelling for a generic refinement framework.
Boswell, R.; Craw, S.
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.
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|
|Peer Reviewed||Peer Reviewed|
|Keywords||Knowledge refinement; Knowledge representation; Knowledge acquisition|
BOSWELL 1999 Knowledge modelling for a generic
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