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    SDM
    2009
    SIAM
    127views Data Mining» more  SDM 2009»
    Event Discovery in Time Series.
    14 years 6 months ago
    Event Discovery in Time Series.
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    The discovery of events in time series can have important implications, such as identifying microlensing events in astronomical surveys, or changes in a patient’s electrocardiog...
    Carla E. Brodley, Dan Preston, Pavlos Protopapas
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    SDM
    2009
    SIAM
    152views Data Mining» more  SDM 2009»
    Non-negative Matrix Factorization, Convexity and Isometry.
    14 years 6 months ago
    Non-negative Matrix Factorization, Convexity and Isometry.
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    In this paper we explore avenues for improving the reliability of dimensionality reduction methods such as Non-Negative Matrix Factorization (NMF) as interpretive exploratory data...
    Nikolaos Vasiloglou, Alexander G. Gray, David V. A...
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    SDM
    2009
    SIAM
    144views Data Mining» more  SDM 2009»
    CORE: Nonparametric Clustering of Large Numeric Databases.
    14 years 6 months ago
    CORE: Nonparametric Clustering of Large Numeric Databases.
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    Current clustering techniques are able to identify arbitrarily shaped clusters in the presence of noise, but depend on carefully chosen model parameters. The choice of model param...
    Andrej Taliun, Arturas Mazeika, Michael H. Bö...
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    SDM
    2009
    SIAM
    125views Data Mining» more  SDM 2009»
    Identifying Unsafe Routes for Network-Based Trajectory Privacy.
    14 years 6 months ago
    Identifying Unsafe Routes for Network-Based Trajectory Privacy.
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    In this paper, we propose a privacy model that offers trajectory privacy to the requesters of Location-Based Services (LBSs), by utilizing an underlying network of user movement. ...
    Aris Gkoulalas-Divanis, Mohamed F. Mokbel, Vassili...
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    SDM
    2009
    SIAM
    162views Data Mining» more  SDM 2009»
    Diversity-Based Weighting Schemes for Clustering Ensembles.
    14 years 6 months ago
    Diversity-Based Weighting Schemes for Clustering Ensembles.
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    Clustering ensembles has been recently recognized as an emerging approach to provide more robust solutions to the data clustering problem. Current methods of clustering ensembles ...
    Andrea Tagarelli, Francesco Gullo, Sergio Greco
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