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Feature representation models are too restricted in that they consider features as dichotomous variables. In an attempt to construct a more general feature model, it is argued that fuzzy set theory (Zadeh, 1965) gives a natural and promising solution to the problem. Using fuzzy set theory in place of ordinary set theory, a fuzzy feature matching model, which is a generalization of Tversky's contrast model (1977) of similarity, is proposed and is applied to the analysis of an asymmetric similarity matrix, which was obtained by asking 42 undergraduates to judge

A fuzzy-set-theoretic feature model and its application to asymmetric similarity data analysis