• DocumentCode
    2500860
  • Title

    Adaptive algorithms for balanced multidimensional clustering

  • Author

    Yu, Clement T. ; Jiang, Tsang Ming

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, IL, USA
  • fYear
    1988
  • fDate
    1-5 Feb 1988
  • Firstpage
    386
  • Lastpage
    393
  • Abstract
    The G-K-D tree (generalized K-D tree) method aims at reducing the average number of data page accesses per query, but it ignores the cost of index search. The authors propose two adaptive algorithms that take into consideration both data page access cost and index page access cost. It attempts to find a minimum total cost. Experimental results indicate that the proposed algorithms are superior to the G-K-D tree method
  • Keywords
    database theory; pattern recognition; trees (mathematics); G-K-D tree; adaptive algorithms; balanced multidimensional clustering; data page access cost; data page accesses per query; generalized K-D tree; index page access cost; index search; Adaptive algorithm; Clustering algorithms; Costs; Databases; Multidimensional systems; Remuneration; Upper bound;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering, 1988. Proceedings. Fourth International Conference on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    0-8186-0827-7
  • Type

    conf

  • DOI
    10.1109/ICDE.1988.105482
  • Filename
    105482