Empirical Analysis and Refinement of Expert System Knowledge Bases.

Knowledge base refinement is the modification of an existing expert system knowledge base with the goals of localizing specific weaknesses in a knowledge base and improving an expert systems performance. Systems that automate some aspects of knowledge base refinement can have a significant impact on the related problems of knowledge base acquisition, maintenance, verification, and learning from experience. The SEEK system was the first expert system framework to integrate large-scale performance information into all phases of knowledge base development and to provide automatic information about rule refinement. A recently developed successor system, SEEK2, significantly expands the scope of the original system in terms of generality and automated capabilities. Based on promising results using the SEEK approach, significant progress can be made in expert system techniques for knowledge acquisition, knowledge base refinement, maintenance, and verification.