Abstract
A close connection between fuzzy set-based (approximate reasoning) methods and the inference principle underlying similarity-based (case-based) reasoning has been pointed out recently [99, 407]. Besides, some attempts at combining case-based reasoning (or, more generally, analogical reasoning) and methods from fuzzy set theory have already been made [408], including the use of fuzzy sets for supporting the computation of similarities of situations in analogical reasoning [144], the formalization of aspects of analogical reasoning by means of similarity relations between fuzzy sets [48], the use of fuzzy set theory in case indexing and retrieval [209, 214], the case-based learning of fuzzy concepts from fuzzy examples [295], the use of fuzzy predicates in the derivation of similarities [40], and the integration of case-based and rule-based reasoning [138]. See [45, 49] for a more general framework of analogical reasoning.
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Hüllermeier, E. (2007). Fuzzy Set-Based Modeling of Case-Based Inference I. In: Case-Based Approximate Reasoning. Theory and Decision Library, vol 44. Springer, Dordrecht. https://doi.org/10.1007/1-4020-5695-8_5
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DOI: https://doi.org/10.1007/1-4020-5695-8_5
Publisher Name: Springer, Dordrecht
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