Abstract
Dynamic data mining is increasingly attracting attention from the respective research community. On the other hand, users of installed data mining systems are also interested in the related techniques and will be even more since most of these installations will need to be updated in the future. For each data mining technique used, we need different methodologies for dynamic data mining. In this paper, we present a methodology for dynamic data mining based on fuzzy clustering. Using the implementation of the proposed system we show its benefits in two application areas: customer segmentation and traffic management.
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