Strong, Fuzzy and Smooth Hierarchical Classification for Case-Based Problem Solving

Jean Lieber 1
1 ORPAILLEUR - Knowledge representation, reasonning
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper explains how case-based problem solving can have benefit from a hierarchical organisation of problems based on a generality relation. Three adaptation-guided retrieval processes are described. The strong classification in a problem hierarchy is a classical deductive process. It is based on the generality relation between problems which organises the hierarchy. The fuzzy classification is a fuzzification of the strong classification. It is based on a fuzzy generality relation between problems, which can be seen as a non-symmetrical similarity measure. The smooth classification extends the fuzzy classification: it is also based on a similarity or dissimilarity measure but takes into account problem and solution adaptation knowledge. These processes have been successfully implemented in two case-based reasoning systems: Resyn/CBR in the domain of organic synthesis and Kasimir/CBR in the domain of cancer treatment.
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Jean Lieber. Strong, Fuzzy and Smooth Hierarchical Classification for Case-Based Problem Solving. 15th European Conference on Artificial Intelligence - ECAI'02, A. Mille, Jul 2002, Lyon, France, pp.81--85. ⟨inria-00107563⟩

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