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» Classes and clusters in data analysis
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ICDE
2007
IEEE
117views Database» more  ICDE 2007»
15 years 11 months ago
Clustering wavelets to speed-up data dissemination in structured P2P MANETs
This paper introduces a fast data dissemination method for structured peer-to-peer networks. The work is motivated on one side by the increase in non-volatile memory available on ...
Mihai Lupu, Jianzhong Li, Beng Chin Ooi, Shengfei ...
ICANN
2010
Springer
14 years 11 months ago
Visualising Clusters in Self-Organising Maps with Minimum Spanning Trees
Abstract. The Self-Organising Map (SOM) is a well-known neuralnetwork model that has successfully been used as a data analysis tool in many different domains. The SOM provides a to...
Rudolf Mayer, Andreas Rauber
ISPASS
2006
IEEE
15 years 4 months ago
Comparing multinomial and k-means clustering for SimPoint
SimPoint is a technique used to pick what parts of the program’s execution to simulate in order to have a complete picture of execution. SimPoint uses data clustering algorithms...
Greg Hamerly, Erez Perelman, Brad Calder
NIPS
2004
14 years 11 months ago
Limits of Spectral Clustering
An important aspect of clustering algorithms is whether the partitions constructed on finite samples converge to a useful clustering of the whole data space as the sample size inc...
Ulrike von Luxburg, Olivier Bousquet, Mikhail Belk...
ADBIS
2007
Springer
132views Database» more  ADBIS 2007»
15 years 4 months ago
Clustering Approach to Generalized Pattern Identification Based on Multi-instanced Objects with DARA
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
Rayner Alfred, Dimitar Kazakov