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ICDM
2002
IEEE
159views Data Mining» more  ICDM 2002»
14 years 9 days ago
O-Cluster: Scalable Clustering of Large High Dimensional Data Sets
Clustering large data sets of high dimensionality has always been a serious challenge for clustering algorithms. Many recently developed clustering algorithms have attempted to ad...
Boriana L. Milenova, Marcos M. Campos
MASS
2010
157views Communications» more  MASS 2010»
13 years 5 months ago
Spatial extension of the Reality Mining Dataset
Data captured from a live cellular network with the real users during their common daily routine help to understand how the users move within the network. Unlike the simulations wi...
Michal Ficek, Lukas Kencl
DPD
2002
125views more  DPD 2002»
13 years 7 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
JIIS
2006
103views more  JIIS 2006»
13 years 7 months ago
Time-focused clustering of trajectories of moving objects
Spatio-temporal, geo-referenced datasets are growing rapidly, and will be more in the near future, due to both technological and social/commercial reasons. From the data mining vie...
Mirco Nanni, Dino Pedreschi
SDM
2010
SIAM
181views Data Mining» more  SDM 2010»
13 years 8 months ago
Making k-means Even Faster
The k-means algorithm is widely used for clustering, compressing, and summarizing vector data. In this paper, we propose a new acceleration for exact k-means that gives the same a...
Greg Hamerly