Abstract
The Authors consider the general problem of similarity and dissimilarity measures in Symbolic Data Analysis. First they examine the classical definitions of elementary event, assertion object, hierarchical dependences and logical dependences, then they consider some well-known measures resemblance measures between two objects (Sokal-Michener, Roger-Tanimoto, Sokal-Sneath, Dice-Czekanowski-Sorenson, Russel-Rao). For resemblance measures based on aggregation functions, the authors consider the proposals of Gowda-Diday, De Baets et al., Malerba et al., Vladutu et al., and Ichino-Yaguchi.
This paper is common job of both the Authors. Paragraphs 1 and 4 are referred to A. Rizzi, while paragraphs 2 and 3 to L. Nieddu
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Nieddu, L., Rizzi, A. (2005). Metrics in Symbolic Data Analysis. In: Bock, HH., et al. New Developments in Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-27373-5_9
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DOI: https://doi.org/10.1007/3-540-27373-5_9
Publisher Name: Springer, Berlin, Heidelberg
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