Abstract
As discussed in the previous volume, the term Data Mining grew from the relentless growth of techniques used to interrogation masses of data. As a myriad of databases emanated from disparate industries, enterprise management insisted their information officers develop methodology to exploit the knowledge held in their repositories. Industry has invested heavily to gain knowledge they can exploit to gain a market advantage. This includes extracting hidden data, trends or pattern from what was traditionally considered noise. For instance most corporations track sales, stock, pay role and other operational information. Acquiring and maintaing these repositories relies on mainstream techniques, technology and methodologies. In this book we discuss a number of founding techniques and expand into intelligent paradigms.
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Holmes, D.E., Tweedale, J., Jain, L.C. (2012). Advanced Modelling Paradigms in Data Mining. In: Holmes, D.E., Jain, L.C. (eds) Data Mining: Foundations and Intelligent Paradigms. Intelligent Systems Reference Library, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23241-1_1
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DOI: https://doi.org/10.1007/978-3-642-23241-1_1
Publisher Name: Springer, Berlin, Heidelberg
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