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Clustering high-dimensional data
Known as:
Subspace clustering
Clustering high-dimensional data is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions. Such high…
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13 relations
Association rule learning
Biclustering
Bioinformatics
Correlation clustering
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Broader (1)
Cluster analysis
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Large-scale Subspace Clustering by Fast Regression Coding
Jun Yu Li
,
Handong Zhao
,
Zhiqiang Tao
,
Y. Fu
International Joint Conference on Artificial…
2017
Corpus ID: 27008349
Large-Scale Subspace Clustering (LSSC) is an interesting and important problem in big data era. However, most existing methods (i…
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2014
2014
Finding the Optimal Subspace for Clustering
Sebastian Goebl
,
Xiao He
,
C. Plant
,
C. Böhm
IEEE International Conference on Data Mining
2014
Corpus ID: 15656547
The ability to simplify and categorize things is one of the most important elements of human thought, understanding, and learning…
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Review
2013
Review
2013
Clustering for High Dimensional Data: Density based Subspace Clustering Algorithms
Sunita Jahirabadkar
,
P. Kulkarni
2013
Corpus ID: 14767856
clusters in high dimensional data is a challenging task as the high dimensional data comprises hundreds of attributes. Subspace…
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2012
2012
Improved subspace clustering via exploitation of spatial constraints
Duc-Son Pham
,
Budhaditya Saha
,
Dinh Q. Phung
,
S. Venkatesh
IEEE Conference on Computer Vision and Pattern…
2012
Corpus ID: 14837200
We present a novel approach to improving subspace clustering by exploiting the spatial constraints. The new method encourages the…
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Highly Cited
2012
Highly Cited
2012
Density-Based Projected Clustering of Data Streams
Marwan Hassani
,
Pascal Spaus
,
M. Gaber
,
T. Seidl
Scalable Uncertainty Management
2012
Corpus ID: 16858139
In this paper, we have proposed, developed and experimentally validated our novel subspace data stream clustering, termed…
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2010
2010
An Improved Initialization Method for Clustering High-Dimensional Data
Yanping Zhang
,
Q. Jiang
International Workshop on Database Technology and…
2010
Corpus ID: 1017106
Searching initial centers in high dimensional space is an interesting and important problem which is relevant for the wide…
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2010
2010
High Performance Dimension Reduction and Visualization for Large High-Dimensional Data Analysis
J. Choi
,
S. Bae
,
Xiaohong Qiu
,
G. Fox
10th IEEE/ACM International Conference on Cluster…
2010
Corpus ID: 8624681
Large high dimension datasets are of growing importance in many fields and it is important to be able to visualize them for…
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2009
2009
An Initialization Method for Clustering High-Dimensional Data
Luying Chen
,
Lifei Chen
,
Q. Jiang
,
Beizhan Wang
,
Liang Shi
First International Workshop on Database…
2009
Corpus ID: 10057554
In iterative refinement clustering algorithms, such as the various types of K-Means algorithms, the clustering results are very…
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2007
2007
Diffusion Maps and Geometric Harmonics for Automatic Target Recognition (ATR). Volume 2. Appendices
S. Zucker
,
R. Coifman
2007
Corpus ID: 33721827
Abstract : Geometric harmonics provides a framework for taking data in high-dimensional measurement spaces and embedding them in…
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2005
2005
Clustering High-Dimensional Data Using Growing SOM
Junlin Zhou
,
Yan Fu
International Symposium on Neural Networks
2005
Corpus ID: 40750100
The self-organizing map (SOM) is a very popular unsupervised neural-network model for analyzing of high-dimensional input data as…
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