Nearest Neighbor Queries for R-Trees: Why Not Bottom-Up?

  • MoonBae Song
  • KwangJin Park
  • SeokJin Im
  • Ki-Sik Kong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3882)


Given a query point q, finding the nearest neighbor (NN) object is one of the most important problem in computer science. In this paper, a bottom-up search algorithm for processing NN query in R-trees is presented. An additional data structure, hash, is introduced to increase the pruning capability of the proposed algorithm. Based on hash, whole data space is disjointly partitioned into n × n cells. Each cell contains the pointers of leaf nodes which intersect with the cell. The experiment shows that the proposed approach outperforms the existing NN search algorithms including the BFS algorithm which is known as I/O optimal algorithm.


Root Node Leaf Node Near Neighbor Query Point Neighbor Query 
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 2006

Authors and Affiliations

  • MoonBae Song
    • 1
  • KwangJin Park
    • 1
  • SeokJin Im
    • 1
  • Ki-Sik Kong
    • 1
  1. 1.Dept. of Computer Science and EngineeringKorea UniversitySeoulKorea

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