• DocumentCode
    2122451
  • Title

    A mining algorithm based on time series association rules

  • Author

    Liping Liu ; Ninghai Cui

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China
  • fYear
    2012
  • fDate
    21-23 April 2012
  • Firstpage
    786
  • Lastpage
    789
  • Abstract
    Based on the concept lattice theory, this paper studies the cycle of association rule mining about the periodic fluctuations of time-series. First of all, do anti-season pretreatment to time-series, then give the algorithm of the generation of the cycle of association rules, and the pruning to the generated concept within algorithm improve the efficiency of the mining speed. And then we can use the given higher precision model to do anti-season changes calculation to those time series which dissatisfy anti-season pretreatment using the moving average method.
  • Keywords
    data mining; time series; antiseason changes calculation; antiseason pretreatment; association rule mining cycle generation; concept lattice theory; mining algorithm; moving average method; periodic fluctuation time series; precision model; time series association rules; Association rules; Data models; Fluctuations; Lattices; Predictive models; Time series analysis; association rules; data mining; formal concept analysis; time-series;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics, Communications and Networks (CECNet), 2012 2nd International Conference on
  • Conference_Location
    Yichang
  • Print_ISBN
    978-1-4577-1414-6
  • Type

    conf

  • DOI
    10.1109/CECNet.2012.6201827
  • Filename
    6201827