CR*-Tree: An Improved R-Tree Using Cost Model

  • Haibo Chen
  • Zhanquan Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3801)

Abstract

We present a cost model for predicting the performance of R-tree and its variants. Optimization base on the cost model can be apply in R-tree construction. we construct a new R-tree variant called CR*-tree using this optimization technique. Experiments have been carried out ,results show that relative error of the cost model is around 12.6%,and the performance for querying CR*-tree has been improved 4.25% by contrast with R*-tree’s.

Keywords

Spatial Data Child Node Cost Model Range Query Spatial Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Haibo Chen
    • 1
  • Zhanquan Wang
    • 2
  1. 1.Department of Computer ScienceZhejiang UniversityHangzhouChina
  2. 2.Department of computer science and engineeringEast China University of Science and TechnologyShanghaiChina

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