Case-Based Reasoning and Model-Based Knowledge Acquisition

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Case-Based Reasoning and Model-Based Knowledge Acquisition
We propose in this paper a general framework for integrating inductive and case-based reasoning techniques for diagnosis tasks. We present a set of practical integrated approaches realised between the KATE-Induction decision tree builder and the PATDEX case-based reasoning system. The specifications of integration are based on the deep understanding about the weak and strong points of each technology. This theoretical knowledge allows specify the structural possibilities of a sound integration of some relevant components of the two techniques. Different levels of integration called cooperative, workbench and seamless approaches involve a tight, medium or strong cooperation between both techniques. Experimental results show the appropriateness of these integrated approaches for the treatment of noisy or unknown data.
Dietmar Janetzko, Gerhard Strube
Added 27 Aug 2010
Updated 27 Aug 2010
Type Conference
Year 1991
Where CKEC
Authors Dietmar Janetzko, Gerhard Strube
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