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TKDE
2002
168views more  TKDE 2002»
13 years 7 months ago
CLARANS: A Method for Clustering Objects for Spatial Data Mining
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. To this end, this paper has three main contrib...
Raymond T. Ng, Jiawei Han
EUROPAR
1999
Springer
13 years 11 months ago
Parallel k/h-Means Clustering for Large Data Sets
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
Kilian Stoffel, Abdelkader Belkoniene
SDM
2008
SIAM
120views Data Mining» more  SDM 2008»
13 years 8 months ago
Spatial Scan Statistics for Graph Clustering
In this paper, we present a measure associated with detection and inference of statistically anomalous clusters of a graph based on the likelihood test of observed and expected ed...
Bei Wang, Jeff M. Phillips, Robert Schreiber, Denn...
ESANN
2000
13 years 8 months ago
Distributed clustering and local regression for knowledge discovery in multiple spatial databases
Many large -scale spatial data analysis problems involve an investigation of relationships in heterogeneous databases. In such situations, instead of making predictions uniformly a...
Aleksandar Lazarevic, Dragoljub Pokrajac, Zoran Ob...
VLDB
1997
ACM
175views Database» more  VLDB 1997»
13 years 11 months ago
STING: A Statistical Information Grid Approach to Spatial Data Mining
Spatial data mining, i.e., discovery of interesting characteristics and patterns that may implicitly exist in spatial databases, is a challenging task due to the huge amounts of s...
Wei Wang 0010, Jiong Yang, Richard R. Muntz