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Introduction to Knowledge Discovery and Data Mining

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Abstract

Knowledge Discovery in Databases (KDD) is an automatic, exploratory analysis and modeling of large data repositories. KDD is the organized process of identifying valid, novel, useful, and understandable patterns from large and complex data sets. Data Mining (DM) is the core of the KDD process, involving the inferring of algorithms that explore the data, develop the model and discover previously unknown patterns. The model is used for understanding phenomena from the data, analysis and prediction.

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Correspondence to Oded Maimon .

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© 2009 Springer Science+Business Media, LLC

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Maimon, O., Rokach, L. (2009). Introduction to Knowledge Discovery and Data Mining. In: Maimon, O., Rokach, L. (eds) Data Mining and Knowledge Discovery Handbook. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09823-4_1

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  • DOI: https://doi.org/10.1007/978-0-387-09823-4_1

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  • Online ISBN: 978-0-387-09823-4

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