A Stochastic Treatment of Similarity

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Conference Proceeding


This study investigates a robust measure of similarity applicable in many domains and across many dimensions of data. Given a distance or discrepancy measure on a domain, the similarity of two values in this domain is defined as the probability that any pair of values from that domain are more different (at a larger distance) than these two values are. We discuss the motivation for this approach, its properties, and the issues that arise from it. © 2010 Springer-Verlag Berlin Heidelberg.

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