Abstract
Abstract: This paper describes a system of shallow and deep knowledge acquisition and representation for diagnostic expert systems. The acquisition system is integrated into a diagnostic expert system shell. Shallow knowledge is represented in a failure model as a set of cause‐effect relations among the possible faults, while deep knowledge is represented in three deep models: a functional, a deep causal and a taxonomic model. The acquisition and the representation of all the models are fully integrated. The deep knowledge is used by the final expert system in order to provide the user with deep explanations of the cause‐effect relations of the failure model.
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