Abstract
This paper gives a description of data mining and its methodology. First, the definition of data mining along with the purposes and growing needs for such a technology are presented. A six-step methodology for data mining is then presented and discussed. The goals and methods of this process are then explained, coupled with a presentation of a number of techniques that are making the data mining process faster and more reliable. These techniques include the use of neural networks and genetic algorithms, which are presented and explained as a way to overcome several complexity problems that the data mining process possesses. A deep survey of the literature is done to show the various purposes and achievements that these techniques have brought to the study of data mining.
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© 2001 Springer Science+Business Media Dordrecht
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Gonzalez, R., Kamrani, A. (2001). A Survey of Methodologies and Techniques for Data Mining and Intelligent Data Discovery. In: Braha, D. (eds) Data Mining for Design and Manufacturing. Massive Computing, vol 3. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-4911-3_2
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DOI: https://doi.org/10.1007/978-1-4757-4911-3_2
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-5205-9
Online ISBN: 978-1-4757-4911-3
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