Second generation knowledge acquisition methods and their application to medicine
Lavrač, Nada ; Mozetič, Igor
First generation expert systems rely on the use of surface knowledge, such as associational of heuristic. This knowledge is typically acquired from domain experts through exhaustive knowledge ...engineering sessions. On the other hand, second generation knowledge acquisition technology is characterized by two main features: the use of deep knowledge and machine learning. In the paper we review three second generation methods that partially automate the knowledge acquisition process: inductive learning of rules from examples, model-based rule learning, and qualitative model acquisition. Results of their application to some medical domains are presented. Finally, we outline different stages of expert system development. An extended expert system shell schema is presented which includes a knowledge acquisition and a knowledge explanaion module.
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