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    ICDE
    2009
    IEEE
    170views Database» more  ICDE 2009»
    On High Dimensional Projected Clustering of Uncertain Data Streams
    14 years 2 months ago
    On High Dimensional Projected Clustering of Uncertain Data Streams
    Download  www.usukita.org
    — In this paper, we will study the problem of projected clustering of uncertain data streams. The use of uncertainty is especially important in the high dimensional scenario, bec...
    Charu C. Aggarwal
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    VLDB
    2004
    ACM
    126views Database» more  VLDB 2004»
    A Framework for Projected Clustering of High Dimensional Data Streams
    14 years 24 days ago
    A Framework for Projected Clustering of High Dimensional Data Streams
    Download  www.charuaggarwal.net
    Charu C. Aggarwal, Jiawei Han, Jianyong Wang, Phil...
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    NN
    2002
    Springer
    144views Neural Networks» more  NN 2002»
    Projective ART for clustering data sets in high dimensional spaces
    13 years 7 months ago
    Projective ART for clustering data sets in high dimensional spaces
    Download  www.math.yorku.ca
    A new neural network architecture (PART) and the resulting algorithm are proposed to
    Yongqiang Cao, Jianhong Wu
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    PR
    2006
    116views more  PR 2006»
    Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data
    13 years 7 months ago
    Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data
    Download  www.disi.unige.it
    Clustering algorithms are routinely used in biomedical disciplines, and are a basic tool in bioinformatics. Depending on the task at hand, there are two most popular options, the ...
    Stefano Rovetta, Francesco Masulli
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    SDM
    2004
    SIAM
    253views Data Mining» more  SDM 2004»
    Density-Connected Subspace Clustering for High-Dimensional Data
    13 years 8 months ago
    Density-Connected Subspace Clustering for High-Dimensional Data
    Download  www.dbs.informatik.uni-muenchen.de
    Several application domains such as molecular biology and geography produce a tremendous amount of data which can no longer be managed without the help of efficient and effective ...
    Peer Kröger, Hans-Peter Kriegel, Karin Kailin...
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