Abstract
Advances in technology and high-throughput experiment techniques have resulted in the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines. Data in terabytes range are not uncommon today and are expected to reach petabytes in the near future for many application domains in science, engineering, business, bioinformatics, and medicine. This has created 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. This talk will provide an overview of a number of data mining research in our group for understanding patterns in global climate system and computational challenges in addressing them.
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© 2007 Springer-Verlag Berlin Heidelberg
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Kumar, V. (2007). High Performance Data Mining - Application for Discovery of Patterns in the Global Climate System. In: Aluru, S., Parashar, M., Badrinath, R., Prasanna, V.K. (eds) High Performance Computing – HiPC 2007. HiPC 2007. Lecture Notes in Computer Science, vol 4873. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77220-0_3
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DOI: https://doi.org/10.1007/978-3-540-77220-0_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77219-4
Online ISBN: 978-3-540-77220-0
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