• DocumentCode
    2850721
  • Title

    Scalable multi-relational association mining

  • Author

    Clare, Amanda ; Williams, Hugh E. ; Lester, Nicholas

  • Author_Institution
    Dept. of Comput. Sci., Wales Univ., Aberystwyth, UK
  • fYear
    2004
  • fDate
    1-4 Nov. 2004
  • Firstpage
    355
  • Lastpage
    358
  • Abstract
    We propose the RADAR technique for multirelational data mining. This permits the mining of very large collections and provides a technique for discovering multirelational associations. Results show that RADAR is reliable and scalable for mining a large yeast homology collection, and that it does not have the main-memory scalability constraints of the Farmer and Warmr tools.
  • Keywords
    data mining; relational databases; RADAR technique; multirelational association discovery; multirelational data mining; scalable multirelational association mining; yeast homology collection mining; Bioinformatics; Computer science; Costs; Data mining; Information retrieval; Information technology; Radar; Scalability; Search engines; Vocabulary;
  • 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.2004.10035
  • Filename
    1410309
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2850721