On Principles of Knowledge Validation

Validation is a critical process in the whole knowledge-based system life cycle. A knowledge base incorporated into such systems has to be verified or (more generally) validated. There have been many approaches to develop specialised procedures and techniques, aimed at assuring the highest level of knowledge quality. Keeping in mind “knowledge validation mappings”, we believe a more global view is necessary to facilitate applying the proper techniques, so the paper deals with practical guidelines of knowledge validation (KV). Facing the most popular techniques of KV: decision tables-based, decision trees-based or nets-based with the criteria set to be utilised, we try to define certain principles useful in the validation procedures referring to two levels: general and detailed. The first one refers to paradigms, which arise from interrelationships among the crucial components of the KV process (procedures, approaches and criteria). The detailed principles are addressed to specific forms used for knowledge representations: rules, frames, neural nets and others.

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