Knowledge modelling for a generic refinement framework.

Boswell, R.; Craw, S.

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
• Electronic ISSN: 1872-7409
• 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