The X-tree : An Index Structure for High-Dimensional Data

  title={The X-tree : An Index Structure for High-Dimensional Data},
  author={Stefan Berchtold and Daniel A. Keim and Hans-Peter Kriegel},
In this paper, we propose a new method for indexing large amounts of point and spatial data in highdimensional space. An analysis shows that index structures such as the R*-tree are not adequate for indexing high-dimensional data sets. The major problem of R-tree-based index structures is the overlap of the bounding boxes in the directory, which increases with growing dimension. To avoid this problem, we introduce a new organization of the directory which uses a split algorithm minimizing… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 14 references

‘ Emient and Efective Querying by Image Content

  • C. Faloutsos, R. Barber, M. Flickner, J. Hafner
  • 1994

Molec - ular Docking Using Shape Descriptors

  • K. ShoichetB., L. BodianD., D. KuntzI.
  • Journal of Computational Chemistry
  • 1992

Method for Points and Rectangles

  • ficient, Rob
  • SIGMOD Int. Conf. on Management of Data, Atlantic…
  • 1990

‘ The Buddy Tree : An Efi - cient and Robust Access Methodfor Spatial Data Base Systems

  • H. Shawney, J Hafner, B. Seeger, Kriegel H.-P.
  • 1990

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