Multi-level clustering and its visualization for exploratory spatial analysis

GeoInformatica

Volumn 6, Issue 2, 2002, Pages 123-152

  Estivill Castro, Vladimir ^a   Lee, Ickjai ^a  

^a UNIVERSITY OF NEWCASTLE   (Australia)

Author keywords

Cluster visualization; Clustering; Data mining; Delaunay diagram; Exploratory spatial analysis

Indexed keywords

COMPUTATIONAL COMPLEXITY; TREES (MATHEMATICS); VECTORS;

SPATIAL ANALYSIS;

ELECTROMAGNETIC FIELD EFFECTS;

GIS; SPATIAL ANALYSIS; VISUALIZATION;

EID: 0036606522     PISSN: 13846175     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1015279009755     Document Type: Article

References (37)

1. Automatic subspace clustering of high dimensional data for data mining applications
2. OPTICS: Ordering points to identify the clustering structure
3. Using angular properties of delaunay triangles to evaluate point patterns
4. Edge length properties of random voronoi polygons
5. Nearest neighbor clutter removal for estimating features in spatial point processes
6. Simple algorithms for enumerating interpoint distances and finding k nearest neighbors
7. Cluster analysis using triangulation
8. A density-based algorithm for discovering clusters in large spatial databases with noise
9. Robust clustering of large geo-referenced data sets
10. How many clusters? Which clustering method? Answers via model-based cluster analysis
11. Problems with handling spatial data - The voronoi approach
12. The meaning of neighbour
13. CURE: An efficient clustering algorithm for large databases
14. ROCK: A robust clustering algorithm for categorical attributes
15. A spatial data mining method by delaunay triangulation
16. CHAMELEON: A hierarchical clustering algorithm using dynamic modeling
17. Computing hierarchies of clusters from the euclidean minimum spanning tree in linear time
18. The first subquadratic algorithm for complete linkage clustering
19. Low degree algorithm for computing and checking gabriel graphs
20. On the homogeneous planar poisson point process
21. Comments of parallel algorithms for hierarchical clustering and cluster validity
22. Efficient and effective clustering method for spatial data mining
23. A mark 1 geographical analysis machine for the automated analysis of point data sets
24. Two exploratory space-time-attribute pattern analysers relevant to GIS
25. Quantitative characterization of second-phase populations
26. A computer movie simulating urban growth in the detroit region
27. STING: A statistical information grid approach to spatial data mining
28. STING +: An approach to active spatial data mining
29. Graph-theoretical methods for detecting and describing gestalt clusters
30. BIRCH: An efficient data clustering method for very large databases