• DocumentCode
    2850637
  • Title

    Matching in frequent tree discovery

  • Author

    Bringmann, Björn

  • Author_Institution
    Lab. of Machine Learning, Freiburg Univ., Germany
  • fYear
    2004
  • fDate
    1-4 Nov. 2004
  • Firstpage
    335
  • Lastpage
    338
  • Abstract
    Various definitions and frameworks for discovering frequent trees in forests have been developed. At the heart of these frameworks lies the notion of matching, which determines when a pattern tree matches a tree in a data set. We introduce a notion of tree matching for use in frequent tree mining and we show that it generalizes the framework of Zaki while still being more specific than that of Termier et al. Furthermore, we show how Zaki´s TreeMinerV algorithm can be adapted towards our notion of tree matching. Experiments show the promise of the approach.
  • Keywords
    data mining; pattern matching; trees (mathematics); TreeMinerV algorithm; frequent tree discovery; tree matching; tree mining; Databases; Formal languages; Frequency; Heart; Machine learning; Pattern matching; Tree graphs; Web mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2004. ICDM '04. Fourth IEEE International Conference on
  • Print_ISBN
    0-7695-2142-8
  • Type

    conf

  • DOI
    10.1109/ICDM.2004.10064
  • Filename
    1410304