Learning to Reene Case Libraries: Initial Results
نویسنده
چکیده
Conversational case-based reasoning (CBR) systems, which incrementally extract a query description through a user-directed conversation , are advertised for their ease of use. However, designing large case libraries that have good performance (i.e., precision and querying ee-ciency) is diicult. CBR vendors provide guidelines for designing these libraries manually, but the guidelines are diicult to apply. We describe an automated inductive approach that revises conversational case libraries to increase their conformance with design guidelines. Revision increased performance on three conversational case libraries.
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