Abstract
Scientific databases are growing in size at such a pace where the traditional techniques for analysis and visualization of the data are no longer adequate in explaining the scientific phenomena actually being captured in the data. Data mining methods are being employed to supplement traditional analysis and visualization techniques to uncover complex patterns deeply imbedded within the ever-growing volumes of observations. This chapter will attempt to stimulate the readers understanding of how data mining methods are being used to uncover some of the mysteries of the universe. The gains being made to uncover complex astronomical phenomena have been largely related to the ability to mine large-scale databases of deep space observations. The chapter will conclude with a review of some of the daunting challenges and opportunities facing professional astronomers and how computational and observational techniques combine in the attempt to reveal the age old questions of how the heavens were formed.
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© 2003 Springer Science+Business Media Dordrecht
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Haydock, M.P. (2003). Data Mining in Astronomy. In: Ciriani, T.A., Fasano, G., Gliozzi, S., Tadei, R. (eds) Operations Research in Space and Air. Applied Optimization, vol 79. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3752-3_9
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DOI: https://doi.org/10.1007/978-1-4757-3752-3_9
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-5242-4
Online ISBN: 978-1-4757-3752-3
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