• DocumentCode
    1526019
  • Title

    Data mining

  • Author

    Olaru, Cristina ; Wehenkel, Louis

  • Author_Institution
    Liege Univ., Belgium
  • Volume
    12
  • Issue
    3
  • fYear
    1999
  • fDate
    7/1/1999 12:00:00 AM
  • Firstpage
    19
  • Lastpage
    25
  • Abstract
    Data mining (DM) is a folkloric denomination of a complex activity that aims at extracting synthesized and previously unknown information from large databases. It denotes also a multidisciplinary field of research and development of algorithms and software environments to support this activity in the context of real-life problems where often huge amounts of data are available for mining. There is a lot of publicity in this field and also different ways to see the things. Hence, depending on the viewpoints, DM is sometimes considered as just a step in a broader overall process called knowledge discovery in databases (KDD), or as a synonym of the latter. This tutorial presents the concept of data mining and aims at providing an understanding of the overall process and tools involved: how the process turns out, what can be done with it, what are the main techniques behind it, and which are the operational aspects. The tutorial also describes a few examples of data mining applications, so as to motivate the power system field as a very opportune data mining application
  • Keywords
    data mining; power system analysis computing; data mining; information extraction; knowledge discovery in databases; large databases; operational aspects; power systems; real-life problems; software environments; Application software; Data analysis; Data mining; Data warehouses; Investments; Power system analysis computing; Power system security; Spinning; Transaction databases; Tutorial;
  • fLanguage
    English
  • Journal_Title
    Computer Applications in Power, IEEE
  • Publisher
    ieee
  • ISSN
    0895-0156
  • Type

    jour

  • DOI
    10.1109/67.773801
  • Filename
    773801