浙江大学学报(英文版)
浙江大學學報(英文版)
절강대학학보(영문판)
JOURNAL OF ZHEJIANG UNIVERSITY SCIENCE
2004年
11期
1405-1412
,共8页
岳士弘%李平%郭继东%周水庚
嶽士弘%李平%郭繼東%週水庚
악사홍%리평%곽계동%주수경
DBSCAN algorithm%Greedy algorithm%Density-skewed cluster
The density-based clustering algorithm presented is different from the classical Density-Based Spatial Clustering of Applications with Noise(DBSCAN)(Ester et al.,1996),and has the following advantages: first,Greedy algorithm substitutes for R*-tree(Bechmann et al.,1990)in DBSCAN to index the clustering space so that the clustering time cost is decreased to great extent and I/O memory load is reduced as well; second,the merging condition to approach to arbitrary-shaped clusters is designed carefully so that a single threshold can distinguish correctly all clusters in a large spatial dataset though some density-skewed clusters live in it. Finally,authors investigate a robotic navigation and test two artificial datasets by the proposed algorithm to verify its effectiveness and efficiency.
