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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
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
Download citation
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
eBook Packages: Springer Book Archive