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

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

Content Provider	Hyper Articles en Ligne (HAL)
Author	Lieber, Jean
Copyright Year	2002
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.
Related Links	https://inria.hal.science/inria-00107563/file/A02-R-129.pdf
Conference Proceedings	15th European Conference on Artificial Intelligence - ECAI'02
Language	English
Publisher	HAL CCSD IOS Press, Amsterdam
Publisher Date	2002-07-01
Access Restriction	Open
Subject Keyword	classification hiérarchique hierarchical classification case-based reasoning classification hiérarchique floue smooth classification raisonnement à partir de cas fuzzy hierarchical classification classification élastique
Content Type	Text
Resource Type	Conference Proceedings
Subject	Computer Science

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