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Название: Proceedings of International Parallel and Distributed Processing Symposium
Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines. This has resulted in an unprecedented opportunity to develop automated data-driven techniques of extracting useful knowledge. Data mining, an important step in this process of knowledge discovery, consists of methods that discover interesting, non-trivial, and useful patterns hidden in the data. The huge size of the available data-sets and their high-dimensionality makes many of the data mining applications computationally very demanding, to the extent that high-performance parallel computing is fast becoming an essential component of the solution. Moreover, the quality of the data mining results often depends directly on the amount of computing resources available. In fact data mining applications are poised to become the dominant consumers of supercomputing in the near future...