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» HD-Eye - Visual Clustering of High dimensional Data
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ICDE
2010
IEEE
222views Database» more  ICDE 2010»
13 years 6 months ago
Finding Clusters in subspaces of very large, multi-dimensional datasets
Abstract— We propose the Multi-resolution Correlation Cluster detection (MrCC), a novel, scalable method to detect correlation clusters able to analyze dimensional data in the ra...
Robson Leonardo Ferreira Cordeiro, Agma J. M. Trai...
EDBT
2008
ACM
132views Database» more  EDBT 2008»
14 years 7 months ago
Indexing high-dimensional data in dual distance spaces: a symmetrical encoding approach
Due to the well-known dimensionality curse problem, search in a high-dimensional space is considered as a "hard" problem. In this paper, a novel symmetrical encoding-bas...
Yi Zhuang, Yueting Zhuang, Qing Li, Lei Chen 0002,...
IPMI
2005
Springer
14 years 8 months ago
Analysis of Event-Related fMRI Data Using Diffusion Maps
The blood oxygen level-dependent (BOLD) signal in response to brief periods of stimulus can be detected using event-related functional magnetic resonance imaging (ER-fMRI). In this...
François G. Meyer, Xilin Shen
PAKDD
2005
ACM
120views Data Mining» more  PAKDD 2005»
14 years 1 months ago
Speeding-Up Hierarchical Agglomerative Clustering in Presence of Expensive Metrics
In several contexts and domains, hierarchical agglomerative clustering (HAC) offers best-quality results, but at the price of a high complexity which reduces the size of datasets ...
Mirco Nanni
SCHOLARPEDIA
2008
89views more  SCHOLARPEDIA 2008»
13 years 6 months ago
Support vector clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur