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Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008)
Subspace Clustering of High Dimensional Data Streams
May 14-May 16
ISBN: 978-0-7695-3131-1
ASCII Text
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Shuyun Wang, Yingjie Fan, Chenghong Zhang, HeXiang Xu, Xiulan Hao, Yunfa Hu, "Subspace Clustering of High Dimensional Data Streams," Computer and Information Science, ACIS International Conference on, pp. 165-170, Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008), 2008.
 
 
BibTex
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@article{ 10.1109/ICIS.2008.58,
author = {Shuyun Wang and Yingjie Fan and Chenghong Zhang and HeXiang Xu and Xiulan Hao and Yunfa Hu},
title = {Subspace Clustering of High Dimensional Data Streams},
journal ={Computer and Information Science, ACIS International Conference on},
volume = {0},
year = {2008},
isbn = {978-0-7695-3131-1},
pages = {165-170},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICIS.2008.58},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Computer and Information Science, ACIS International Conference on
TI - Subspace Clustering of High Dimensional Data Streams
SN - 978-0-7695-3131-1
SP165
EP170
A1 - Shuyun Wang,
A1 - Yingjie Fan,
A1 - Chenghong Zhang,
A1 - HeXiang Xu,
A1 - Xiulan Hao,
A1 - Yunfa Hu,
PY - 2008
KW - Cluster
KW - subspace
KW - Data stream
KW - high-dimensional
VL - 0
JA - Computer and Information Science, ACIS International Conference on
ER -
 
In this paper, SOStream, which is a novel algorithm of clustering over high dimensional online data stream is presented, it is based on subspace. SOStream partitions the data space into grids, and maintains a superset of all dense units in an online way. A deterministic lower and upper bound of the selectivity of each maintained units are also given. With the maintained potential dense units, SOStream is capable of discovering the clusters in different subspaces over high dimensional data stream with arbitrary shape. The experimental results on real and synthetic datasets demonstrate the effectivity of the approach.
Index Terms:
Cluster, subspace, Data stream, high-dimensional
Citation:
Shuyun Wang, Yingjie Fan, Chenghong Zhang, HeXiang Xu, Xiulan Hao, Yunfa Hu, "Subspace Clustering of High Dimensional Data Streams," icis, pp.165-170, Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008), 2008
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