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    DMIN
    2008
    152views Data Mining» more  DMIN 2008»
    PCS: An Efficient Clustering Method for High-Dimensional Data
    13 years 6 months ago
    PCS: An Efficient Clustering Method for High-Dimensional Data
    Download  www.cs.uml.edu
    Clustering algorithms play an important role in data analysis and information retrieval. How to obtain a clustering for a large set of highdimensional data suitable for database ap...
    Wei Li 0011, Cindy Chen, Jie Wang
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    BMEI
    2008
    IEEE
    222views Biomedical Imaging» more  BMEI 2008»
    Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
    13 years 6 months ago
    Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
    Download  math.georgiasouthern.edu
    The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...
    Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wun...
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    SDM
    2004
    SIAM
    253views Data Mining» more  SDM 2004»
    Density-Connected Subspace Clustering for High-Dimensional Data
    13 years 6 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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    APWEB
    2006
    Springer
    210views Internet Technology» more  APWEB 2006»
    Generalized Projected Clustering in High-Dimensional Data Streams
    13 years 8 months ago
    Generalized Projected Clustering in High-Dimensional Data Streams
    Download  www.cc.gatech.edu
    Clustering is to identify densely populated subgroups in data, while correlation analysis is to find the dependency between the attributes of the data set. In this paper, we combin...
    Ting Wang
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    SDM
    2003
    SIAM
    184views Data Mining» more  SDM 2003»
    Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
    13 years 5 months ago
    Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
    Download  www-users.cs.umn.edu
    The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
    Levent Ertöz, Michael Steinbach, Vipin Kumar
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