Expert system validation through knowledge base refinement

Authors:
Pedro Meseguer
Affiliations:
Departament de Llenguatges i Sistemes Informatics, Universitat Politecnica de Catalunya, Barcelona, Spain and Institut d'Investigacio en Intelligencia Artificial, C.S.I.C., Blanes, Girona, Spain
Venue:
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Year:
1993

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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 is being used to validate a real ES and some empirical results are given.