• DocumentCode
    606037
  • Title

    Data mining with time granules

  • Author

    Tzung-Pei Hong ; Guo-Cheng Lan ; Pei-Shan Wu ; Shyue-liang Wang

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
  • fYear
    2012
  • fDate
    23-25 Oct. 2012
  • Firstpage
    673
  • Lastpage
    677
  • Abstract
    Most of the existing studies only consider different item lifespans to find general temporal association rules, and this may neglect some useful information. In this paper, the concept of a hierarchy of time periods is considered and a new kind of rules, called hierarchical temporal rules, is proposed. The lifespan of an item in a time granule is calculated from its first appearance time to the end time in the time granule. The experimental results on a simulation dataset show the performance of the proposed algorithm under the new item lifespan.
  • Keywords
    data mining; appearance time; data mining; end time; general temporal association rules; hierarchical temporal rules; item lifespans; time granules; time period hierarchy; Data mining; a hierarchy of time granules; association-rule mining; item lifespan; temporal association rules;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Service Science and Data Mining (ISSDM), 2012 6th International Conference on New Trends in
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4673-0876-2
  • Type

    conf

  • Filename
    6528717