Accession Number : ADA192913

Title :   Empirical Analysis and Refinement of Expert System Knowledge Bases.

Descriptive Note : Quarterly rept.,

Corporate Author : RUTGERS - THE STATE UNIV NEW BRUNSWICK NJ CENTER FOR EXPERT SYSTEMS RESEARCH

Personal Author(s) : Weiss, Sholom M

PDF Url : ADA192913

Report Date : 29 Feb 1988

Pagination or Media Count : 5

Abstract : 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 system's 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.

Descriptors :   *INFORMATION RETRIEVAL, *ARTIFICIAL INTELLIGENCE, ACQUISITION, AUTOMATION, EXPERIMENTAL DATA, LEARNING, REFINING

Subject Categories : Cybernetics
      Information Science

Distribution Statement : APPROVED FOR PUBLIC RELEASE