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KDD
2002
ACM
155views Data Mining» more  KDD 2002»
14 years 5 months ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui
VLDB
1998
ACM
312views Database» more  VLDB 1998»
13 years 8 months ago
WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases
Many applications require the management of spatial data. Clustering large spatial databases is an important problem which tries to find the densely populated regions in the featu...
Gholamhosein Sheikholeslami, Surojit Chatterjee, A...
SIGMOD
1999
ACM
183views Database» more  SIGMOD 1999»
13 years 9 months ago
OPTICS: Ordering Points To Identify the Clustering Structure
Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysi...
Mihael Ankerst, Markus M. Breunig, Hans-Peter Krie...
SIGMOD
1998
ACM
99views Database» more  SIGMOD 1998»
13 years 9 months ago
CURE: An Efficient Clustering Algorithm for Large Databases
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...
Sudipto Guha, Rajeev Rastogi, Kyuseok Shim
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 6 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar