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» Visualising the Cluster Structure of Data Streams
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CIKM
2006
Springer
13 years 8 months ago
Adaptive non-linear clustering in data streams
Data stream clustering has emerged as a challenging and interesting problem over the past few years. Due to the evolving nature, and one-pass restriction imposed by the data strea...
Ankur Jain, Zhihua Zhang, Edward Y. Chang
NN
2002
Springer
226views Neural Networks» more  NN 2002»
13 years 4 months ago
Data visualisation and manifold mapping using the ViSOM
The self-organising map (SOM) has been successfully employed as a nonparametric method for dimensionality reduction and data visualisation. However, for visualisation the SOM requ...
Hujun Yin
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 5 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
ISVC
2010
Springer
13 years 3 months ago
Subversion Statistics Sifter
We present Subversion Statistics Sifter, a visualisation and statistics system for exploring the structure and evolution of data contained in Subversion repositories with respect t...
Christoph Müller, Guido Reina, Michael Burch,...
ICDM
2009
IEEE
167views Data Mining» more  ICDM 2009»
13 years 2 months ago
Self-Adaptive Anytime Stream Clustering
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited...
Philipp Kranen, Ira Assent, Corinna Baldauf, Thoma...