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DEXA
2009
Springer
151views Database» more  DEXA 2009»
13 years 12 months ago
Detecting Projected Outliers in High-Dimensional Data Streams
Abstract. In this paper, we study the problem of projected outlier detection in high dimensional data streams and propose a new technique, called Stream Projected Ouliter deTector ...
Ji Zhang, Qigang Gao, Hai H. Wang, Qing Liu, Kai X...
CORR
2010
Springer
219views Education» more  CORR 2010»
13 years 5 months ago
Clustering high dimensional data using subspace and projected clustering algorithms
: Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. Subspace clustering enumerate...
Rahmat Widia Sembiring, Jasni Mohamad Zain, Abdull...
ICML
2003
IEEE
14 years 6 months ago
Random Projection for High Dimensional Data Clustering: A Cluster Ensemble Approach
We investigate how random projection can best be used for clustering high dimensional data. Random projection has been shown to have promising theoretical properties. In practice,...
Xiaoli Zhang Fern, Carla E. Brodley
SIGMOD
2000
ACM
165views Database» more  SIGMOD 2000»
13 years 9 months ago
Finding Generalized Projected Clusters In High Dimensional Spaces
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
Charu C. Aggarwal, Philip S. Yu
NN
2002
Springer
144views Neural Networks» more  NN 2002»
13 years 5 months ago
Projective ART for clustering data sets in high dimensional spaces
A new neural network architecture (PART) and the resulting algorithm are proposed to
Yongqiang Cao, Jianhong Wu