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Erschienen in:
2008 | OriginalPaper | Buchkapitel
Case-Based Reasoning Using Gradual Rules Induced from Dominance-Based Rough Approximations
verfasst von : Salvatore Greco, Benedetto Matarazzo, Roman Słowiński
Erschienen in: Rough Sets and Knowledge Technology
Verlag: Springer Berlin Heidelberg
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Case-based reasoning (CBR) regards the inference of some proper conclusions related to a new situation by the analysis of similar cases from a memory of previous cases. We propose to represent similarity by gradual decision rules induced from rough approximations of fuzzy sets. Indeed, we are adopting the Dominance-based Rough Set Approach (DRSA) that is particularly appropriate in this context for its ability of handling monotonicity relationship of the type “the more similar is object
y
to object
x
, the more credible is that
y
belongs to the same set as
x
”. At the level of marginal similarity concerning single features, we consider only ordinal properties of similarity, and for the aggregation of marginal similarities, we use a set of gradual decision rules based on the general monotonicity property of comprehensive similarity with respect to marginal similarities. We present formal properties of rough approximations used for CBR.