• DocumentCode
    3259769
  • Title

    Full Perfect Extension Pruning for Frequent Graph Mining

  • Author

    Borgelt, Christian ; Meinl, Thorsten

  • Author_Institution
    Eur. Center for Soft Comput., Mieres
  • fYear
    2006
  • fDate
    Dec. 2006
  • Firstpage
    263
  • Lastpage
    268
  • Abstract
    Mining graph databases for frequent subgraphs has recently developed into an area of intensive research. Its main goals are to reduce the execution time of the existing basic algorithms and to enhance their capability to find meaningful graph fragments. Here we present a method to achieve the former, namely an improvement of what we called "perfect extension pruning" in an earlier paper (Borgelt, 2004). With it the number of generated fragments and visited search tree nodes can be reduced, thus accelerating the search
  • Keywords
    data mining; trees (mathematics); graph mining; perfect extension pruning; search tree nodes; Acceleration; Algorithm design and analysis; Biochemical analysis; Biochemistry; Databases; Frequency; Information science; Logic programming; Tree graphs; Web mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    0-7695-2702-7
  • Type

    conf

  • DOI
    10.1109/ICDMW.2006.82
  • Filename
    4063636