On the one hand, clustering methods are of a particular interest to automatically identify the inner structure of a data set. On the other hand, fuzzy partitions are particularly suitable to define a subjective and domain dependent vocabulary that may then be used to personalize an information system. To make the translation of raw data into knowledge easier, we propose in this paper to generate personalized linguistic and graphical explanations of a cluster-based data structure.
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