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KDD
2007
ACM
178views Data Mining» more  KDD 2007»
15 years 10 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
79
Voted
VTC
2006
IEEE
129views Communications» more  VTC 2006»
15 years 4 months ago
A Framework for Automatic Clustering of Parametric MIMO Channel Data Including Path Powers
— We present a solution to the problem of identifying clusters from MIMO measurement data in a data window, with a minimum of user interaction. Conventionally, visual inspection ...
Nicolai Czink, Pierluigi Cera, Jari Salo, Ernst Bo...
93
Voted
MCS
2001
Springer
15 years 2 months ago
Finding Consistent Clusters in Data Partitions
Abstract. Given an arbitrary data set, to which no particular parametrical, statistical or geometrical structure can be assumed, different clustering algorithms will in general pr...
Ana L. N. Fred
90
Voted
SSDBM
2005
IEEE
218views Database» more  SSDBM 2005»
15 years 3 months ago
The "Best K" for Entropy-based Categorical Data Clustering
With the growing demand on cluster analysis for categorical data, a handful of categorical clustering algorithms have been developed. Surprisingly, to our knowledge, none has sati...
Keke Chen, Ling Liu
94
Voted
PRL
2006
139views more  PRL 2006»
14 years 10 months ago
Adaptive Hausdorff distances and dynamic clustering of symbolic interval data
This paper presents a partitional dynamic clustering method for interval data based on adaptive Hausdorff distances. Dynamic clustering algorithms are iterative two-step relocatio...
Francisco de A. T. de Carvalho, Renata M. C. R. de...