Abstract
Measuring similarity is an important task in many domains such as psychology, taxonomy, information retrieval, image processing, bioinformatics, and so on. The diversity of domains has led to many different definitions of and methods for determining similarity. Even within fuzzy set theory, how to measure similarity between fuzzy sets presents a wide variety of approaches depending on what characteristic of a fuzzy set is emphasized, for example, set-based, logic-based or geometric-based views of a fuzzy set. First similarity is examined from a psychological viewpoint, and how that perspective might be applicable to fuzzy set similarity measures is explored. Then two fuzzy set similarity measures, one set-based and the other geometric-based, are reviewed, and a comparison is made between the two.
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Cross, V. (2018). Relating Fuzzy Set Similarity Measures. In: Melin, P., Castillo, O., Kacprzyk, J., Reformat, M., Melek, W. (eds) Fuzzy Logic in Intelligent System Design. NAFIPS 2017. Advances in Intelligent Systems and Computing, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-319-67137-6_2
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DOI: https://doi.org/10.1007/978-3-319-67137-6_2
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