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A fuzzy logic based similarity measure is introduced as a criterion for the identification of structure in data. An important characteristic of the proposed approach is that cluster prototypes are formed and evaluated in the course of the optimization without any a-priori assumptions about the number of clusters. The intuitively straightforward compound optimization criterion of maximizing the overall similarity between data and the prototypes while minimizing the similarity between thedoi:10.1109/cmpsac.2002.1045169 dblp:conf/compsac/BargielaPH02 fatcat:otbxcwr63rednk3xrsucz47hpa