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Efficient Filter Algorithms for Reverse k-Nearest Neighbor Query

  • Shengsheng Wang
  • Qiannan Lv
  • Dayou Liu
  • Fangming Gu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6897)

Abstract

Reverse k-Nearest Neighbor (RkNN) Queries have got considerable attentions over the recent years. Most state of the art methods use the two-step (filter-refinement) RkNN processing. However, for a large k, the amount of calculation becomes very heavy, especially in the filter step. This is not acceptable for most mobile devices. A new filter strategy called BRC is proposed to deal with the filter step for RkNN queries. There are two pruning heuristics in BRC. The experiments show that the processing time of BRC is still acceptable for most mobile devices when k is large. And we extend the BRC to the continuous RkNN queries.

Keywords

Reverse k-Nearest Neighbor Continuous Reverse k-Nearest Neighbor Spatial Database 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Shengsheng Wang
    • 1
  • Qiannan Lv
    • 1
  • Dayou Liu
    • 1
  • Fangming Gu
    • 1
  1. 1.College of Computer Science and TechnologyJilin UniversityChangchunChina

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