• DocumentCode
    2864217
  • Title

    An Evolutionary Mining Model in Incremental Data Mining

  • Author

    Jiancong, Fan ; Yongquan, Liang ; Jiuhong, Ruan

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Shandong Univ. of Sci. & Technol., Qingdao, China
  • Volume
    3
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    114
  • Lastpage
    118
  • Abstract
    Incremental data mining is very important to solve the temporal dynamic property of knowledge, improve the performance of mining processes and efficiency of mining results. Incremental data occurs with the passage of time. Evolutionary methods can be adopted to solve such increment. A multiply evolutionary model is built to describe incremental data evolutionary mining processes. Copy operator, cross operator and mutation operator are designed. A general algorithm for dynamic evolutionary mining is also presented. The experiments showed that the evolutionary incremental data mining method could solve the scalable problem of data mining better, and have high accuracy and good time performance.
  • Keywords
    data mining; evolutionary computation; cross operator; dynamic evolutionary mining; incremental data mining; multiply evolutionary model; mutation operator; Association rules; Computer science; Data engineering; Data mining; Educational institutions; Evolution (biology); Information science; Iterative algorithms; Knowledge engineering; Space technology; data mining; evolutionary model; evolutionary strategy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.488
  • Filename
    5366247