• DocumentCode
    3230793
  • Title

    An improved algorithm of mining Strong Jumping Emerging Patterns based on sorted SJEP-Tree

  • Author

    Chen, Xiangtao ; Lu, Lijuan

  • Author_Institution
    Sch. of Comput. & Commun., Hunan Univ., Changsha, China
  • fYear
    2010
  • fDate
    23-26 Sept. 2010
  • Firstpage
    894
  • Lastpage
    898
  • Abstract
    Jumping Emerging Patterns (JEPs) are a data mining model that is useful as a mean of discovering differences present amongst a collection of classified transaction datasets. However, current JEPs mining algorithms are usually time-consuming and pruning with minimum support may require several adjustments. In this paper, we investigate Strong Jumping Emerging Patterns (SJEPs), which are believed to be high quality patterns with the most differentiating power. We propose an improved tree-based method to effectively mine SJEPs of two data classes. Experimental results show that our algorithm is effective.
  • Keywords
    data mining; pattern classification; transaction processing; trees (mathematics); classified transaction dataset; data class; data mining; sorted SJEP-tree; strong jumping emerging pattern mining; tree-based method; ISO standards; Iris; Liver; data mining; jumping emerging patterns; strong jumping emerging patterns;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-6437-1
  • Type

    conf

  • DOI
    10.1109/BICTA.2010.5645245
  • Filename
    5645245