• DocumentCode
    2834797
  • Title

    A Framework of an Automated Data Mining System Using Autonomous Intelligent Agents

  • Author

    Rajan, J. ; Saravanan, V.

  • Author_Institution
    Dept. of Comput. Applic., Karunya Univ., Coimbatore
  • fYear
    2008
  • fDate
    Aug. 29 2008-Sept. 2 2008
  • Firstpage
    700
  • Lastpage
    704
  • Abstract
    Data mining is the analysis of (often large) observational data sets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and useful to the data owner. In other words data mining is a process of finding previously unknown, profitable and use patterns hidden in data, with no prior hypothesis. Automated Data Mining and modeling software gives managers a tool to perform analyses that otherwise would need to be handled by a highly trained researcher. Automated data mining methodologies is not to provide more accurate results but strives to empower non-expert users to achieve reasonable results with minimum effort. Data mining is a difficult and laborious activity that requires a great deal of expertise for obtaining quality results. We need new methods for intelligent data analysis to extract relevant information with less effort. With the use of the autonomous intelligent agents several data mining steps are possibly be automated. The goal is to empower non-expert users to achieve reasonable results with minimum effort. In this paper we present an automated approach for a data mining system using autonomous intelligent agents.
  • Keywords
    data mining; software agents; automated data mining system; autonomous intelligent agents; data analysis; Application software; Computer applications; Computer science; Data mining; Databases; Information analysis; Information technology; Intelligent agent; Software performance; Software tools; Automated; Data Mining; Intelligent Agents;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology, 2008. ICCSIT '08. International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-0-7695-3308-7
  • Type

    conf

  • DOI
    10.1109/ICCSIT.2008.167
  • Filename
    4624958