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A Clustering Method for Optimizing Spatial Locality  

김홍기 (동신대학교 컴퓨터학과)
Publication Information
Journal of KIISE:Databases / v.31, no.2, 2004 , pp. 83-90 More about this Journal
Abstract
In this paper, we study the CCD(Clustering with Circular Distance) and the COD(Clustering with Obstructed Distance) problems to be considered when objects are being clustered in a circularly search space and a search space with the presence of obstacles. We also propose a now clustering algorithm for clustering efficiently objects that the insertion or the deletion is occurring frequently in multi-dimensional search space. The distance function for solving the CCD and COD Problems is defined in the Proposed clustering algorithm. This algorithm is included a clustering method to create clusters that have a high spatial locality by minimum computation time.
Keywords
Clustering; Circular Distance; Obstructed Distance; Spatial Locality; Modified Hierarchical Variance;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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