TitleExpert system validation through knowedge base refinement
Publication TypeJournal Article
Year of Publication1996
AuthorsMeseguer P, Verdaguer A
JournalInternational Journal of Intelligent Systems
Volume11
Number7
Pagination429-462
Abstract

Knowledge base (KB) refinement is a suitable technique to support expert system (ES) validation. When used for validation, KB refinement should be guided not only by the number of errors to solve but also by the importance of those errors. Most serious errors should be solved first, even causing other errors of lower importance but assuring a neat validity gain. These are the bases for IMPROVER, a KB refinement tool designed to support ES validation. IMPROVER refines ES for medical diagnosis with this classification of error importance: false negative > false positive > ordering mismatch. IMPROVER has been used to support the validation of PNEUMON-IA, a real ES on the medical domain. After refinement, the ES validity has increased substantially. Detailed evidence of this improvement is provided, as well as examples of how the refinement process was performed.