A Density-Based K-Nearest Neighbors Search Method

  • Jang I. S. (Telematics Research Division, ETRI) ;
  • Min K.W. (Telematics Research Division, ETRI) ;
  • Choi W.S (Telematics Research Division, ETRI)
  • Published : 2004.10.01

Abstract

Spatial database system provides many query types and most of them are required frequent disk I/O and much CPU time. k-NN search is to find k-th closest object from the query point and up to now, several k-NN search methods have been proposed. Among these, MINMAX distance method has an aim not to visit unnecessary node by applying pruning technique. But this method access more disk than necessary while pruning unnecessary node. In this paper, we propose new k-NN search algorithm based on density of object. With this method, we predict the radius to be expected to contain k-NN object using density of data set and search those objects within this radius and then adjust radius if failed. Experimental results show that this method outperforms the previous MINMAX distance method. This algorithm visit fewer disks than MINMAX method by the factor of maximum $22\%\;and\;average\;6\%.$

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