Robert A. Weida

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Terminological systems, such as KL-ONE and K-Rep, are widely used in AI to represent and reason with concept descriptions. They compute subsumption relations between concepts and automaticallyclassify concepts into a taxonomy. Each concept in the taxonomy describes a set of possible instances which are a superset of those described by its descendants. One(More)
The K-Rep system was built to explore the utility of a KL-One style knowledge representation in the development of expert systems. Beginning in about 1985, our activity in expert systems has been centered on the FAME (FinAncial Marketing Expertise) system[4]. FAME attempts to provide support to an IBM marketing representative in the financing decisions(More)
We introduce a predictive concept recognition methodology for description logics based on a new closed terminology assumption. During knowledge engineering, our system adopts the standard open terminology assumption as it automatically classifies concept descriptions into a taxonomy via subsumption inferences. However, for applications like configuration,(More)