The KDD process for extracting useful knowledge from volumes of data

  title={The KDD process for extracting useful knowledge from volumes of data},
  author={Usama M. Fayyad and Gregory Piatetsky-Shapiro and Padhraic Smyth},
  journal={Commun. ACM},
AS WE MARCH INTO THE AGE of digital information, the problem of data overload looms ominously ahead. Our ability to analyze and understand massive datasets lags far behind our ability to gather and store the data. A new generation of computational techniques and tools is required to support the extraction of useful knowledge from the rapidly growing volumes of data. These techniques and tools are the subject of the emerging field of knowledge discovery in databases (KDD) and data mining. Large… 

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  • Additional references for this article can be found at DM-refs

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