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DATAMINE
1999
113views more  DATAMINE 1999»
13 years 5 months ago
A Fast Parallel Clustering Algorithm for Large Spatial Databases
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,...
Xiaowei Xu, Jochen Jäger, Hans-Peter Kriegel
PAMI
2010
164views more  PAMI 2010»
13 years 3 months ago
Large-Scale Discovery of Spatially Related Images
— We propose a randomized data mining method that finds clusters of spatially overlapping images. The core of the method relies on the min-Hash algorithm for fast detection of p...
Ondrej Chum, Jiri Matas
ICDE
1998
IEEE
122views Database» more  ICDE 1998»
14 years 6 months ago
A Distribution-Based Clustering Algorithm for Mining in Large Spatial Databases
Xiaowei Xu, Martin Ester, Hans-Peter Kriegel, J&ou...
ICDM
2006
IEEE
108views Data Mining» more  ICDM 2006»
13 years 11 months ago
Spatial Multidimensional Sequence Clustering
Measurements at different time points and positions in large temporal or spatial databases requires effective and efficient data mining techniques. For several parallel measureme...
Ira Assent, Ralph Krieger, Boris Glavic, Thomas Se...
DPD
2002
125views more  DPD 2002»
13 years 5 months ago
Parallel Mining of Outliers in Large Database
Data mining is a new, important and fast growing database application. Outlier (exception) detection is one kind of data mining, which can be applied in a variety of areas like mon...
Edward Hung, David Wai-Lok Cheung