Density-based clustering in spatial databases: The algorithm GDBSCAN and its applications

被引：968
作者：
Sander, J [1 ]
Ester, M [1 ]
Kriegel, HP [1 ]
Xu, XW [1 ]
机构：
[1] Univ Munich, Inst Comp Sci, D-80538 Munich, Germany
来源：
DATA MINING AND KNOWLEDGE DISCOVERY | 1998年 / 2卷 / 02期
关键词：
clustering algorithms; spatial databases; efficiency; applications;
D O I：
10.1023/A:1009745219419
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The clustering algorithm DBSCAN relies on a density-based notion of clusters and is designed to discover clusters of arbitrary shape as well as to distinguish noise. In this paper, we generalize this algorithm in two important directions. The generalized algorithm-called GDBSCAN-can cluster point objects as well as spatially extended objects according to both, their spatial and their nonspatial attributes. In addition, four applications using 2D points (astronomy), 3D points (biology), 5D points (earth science) and 2D polygons (geography) are presented, demonstrating the applicability of GDBSCAN to real-world problems.
引用
收藏
页码：169 / 194
页数：26
相关论文
共 27 条
[1]  
[Anonymous], REMOTE SENSING DIGIT
[2]  
[Anonymous], 1990, PATTERN ANAL UNDERST
[3]   THE FIRST SURVEY - FAINT IMAGES OF THE RADIO SKY AT 20 CENTIMETERS [J].
BECKER, RH ;
WHITE, RL ;
HELFAND, DJ .
ASTROPHYSICAL JOURNAL, 1995, 450 (02) :559-577
[4]  
BECKMANN N, 1990, SIGMOD REC, V19, P322, DOI 10.1145/93605.98741
[5]   PROTEIN DATA BANK - COMPUTER-BASED ARCHIVAL FILE FOR MACROMOLECULAR STRUCTURES [J].
BERNSTEIN, FC ;
KOETZLE, TF ;
WILLIAMS, GJB ;
MEYER, EF ;
BRICE, MD ;
RODGERS, JR ;
KENNARD, O ;
SHIMANOUCHI, T ;
TASUMI, M .
JOURNAL OF MOLECULAR BIOLOGY, 1977, 112 (03) :535-542
[6]  
BRINKHOFF T, 1994, P ACM SIGMOD INT C M, P197
[7]  
CONNOLLY ML, 1986, J MOL GRAPHICS, V4, P3
[8]  
Ester M., 1997, Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, P10
[9]  
ESTER M, 1995, P 1 INT C KNOWL DISC, P94
[10]  
Guting R.H., 1994, Vldb J, V3, P357, DOI DOI 10.1007/BF01231602
123