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    SDM
    2009
    SIAM
    193views Data Mining» more  SDM 2009»
    Agglomerative Mean-Shift Clustering via Query Set Compression.
    15 years 6 months ago
    Agglomerative Mean-Shift Clustering via Query Set Compression.
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    Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets...
    Xiaotong Yuan, Bao-Gang Hu, Ran He
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    SDM
    2009
    SIAM
    215views Data Mining» more  SDM 2009»
    Hybrid Clustering of Text Mining and Bibliometrics Applied to Journal Sets.
    15 years 6 months ago
    Hybrid Clustering of Text Mining and Bibliometrics Applied to Journal Sets.
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    To obtain correlated and complementary information contained in text mining and bibliometrics, hybrid clustering to incorporate textual content and citation information has become...
    Bart De Moor, Frizo A. L. Janssens, Shi Yu, Wolfga...
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    SDM
    2009
    SIAM
    291views Data Mining» more  SDM 2009»
    Detection and Characterization of Anomalies in Multivariate Time Series.
    15 years 6 months ago
    Detection and Characterization of Anomalies in Multivariate Time Series.
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    Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
    Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...
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    SDM
    2009
    SIAM
    140views Data Mining» more  SDM 2009»
    Straightforward Feature Selection for Scalable Latent Semantic Indexing.
    15 years 6 months ago
    Straightforward Feature Selection for Scalable Latent Semantic Indexing.
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    Latent Semantic Indexing (LSI) has been validated to be effective on many small scale text collections. However, little evidence has shown its effectiveness on unsampled large sca...
    Jun Yan, Shuicheng Yan, Ning Liu, Zheng Chen
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    SDM
    2009
    SIAM
    208views Data Mining» more  SDM 2009»
    A Bayesian Approach Toward Finding Communities and Their Evolutions in Dynamic Social Networks.
    15 years 6 months ago
    A Bayesian Approach Toward Finding Communities and Their Evolutions in Dynamic Social Networks.
    Download  www.nec-labs.com
    Although a large body of work are devoted to finding communities in static social networks, only a few studies examined the dynamics of communities in evolving social networks. I...
    Tianbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong, ...
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