An integration of knowledge and data representation

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[[abstract::A variety of types of linkages from knowledge bases to databases have been proposed and a few have heen implemented [Miss84]. In this research note we summarize a technique which was employed in a specific context: knowledge extraction from a copy of an existing clinical database. The knowledge base is also used to drive the extracting process. RX builds causal models in its domain to generate input from statistical hypothesis verification. We distinguish two information types: knowledge and data, and recognize four types of knowledge; categorical, definitional, causal (represented in frames), and operational, represented by rules. Based on our experience we speculate about the generalization of the approach.|]]

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abstract: A variety of types of linkages from knowledge bases to databases have been proposed and a few have heen implemented [Miss84]. In this research note we summarize a technique which was employed in a specific context: knowledge extraction from a copy of an existing clinical database. The knowledge base is also used to drive the extracting process. RX builds causal models in its domain to generate input from statistical hypothesis verification. We distinguish two information types: knowledge and data, and recognize four types of knowledge; categorical, definitional, causal (represented in frames), and operational, represented by rules. Based on our experience we speculate about the generalization of the approach.

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