Abstract
Tversky [221] noted that “most theoretical and empirical analyses of similarity assume that objects can be adequately represented as points in some coordinate space and that dissimilarity behaves like a distance function.” While Tversky’s observation concerned objects as crisp values, the notion of proximity defining similarity can also be used to assess the similarity of fuzzy sets. For fuzzy sets, the distance is not between points but rather between membership functions. In this chapter we consider three methods for producing metric based similarity measures.
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© 2002 Springer-Verlag Berlin Heidelberg
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Cross, V.V., Sudkamp, T.A. (2002). Proximity-Based Measures. In: Similarity and Compatibility in Fuzzy Set Theory. Studies in Fuzziness and Soft Computing, vol 93. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1793-5_8
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DOI: https://doi.org/10.1007/978-3-7908-1793-5_8
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-2507-7
Online ISBN: 978-3-7908-1793-5
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