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    SDM
    2009
    SIAM
    205views Data Mining» more  SDM 2009»
    Identifying Information-Rich Subspace Trends in High-Dimensional Data.
    16 years 1 months ago
    Identifying Information-Rich Subspace Trends in High-Dimensional Data.
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    Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
    Chandan K. Reddy, Snehal Pokharkar
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    SDM
    2009
    SIAM
    331views Data Mining» more  SDM 2009»
    Privacy Preservation in Social Networks with Sensitive Edge Weights.
    16 years 1 months ago
    Privacy Preservation in Social Networks with Sensitive Edge Weights.
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    With the development of emerging social networks, such as Facebook and MySpace, security and privacy threats arising from social network analysis bring a risk of disclosure of con...
    Jie Wang, Jinze Liu, Jun Zhang, Lian Liu
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    SDM
    2009
    SIAM
    125views Data Mining» more  SDM 2009»
    Identifying Unsafe Routes for Network-Based Trajectory Privacy.
    16 years 1 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.
    16 years 1 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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    SDM
    2009
    SIAM
    167views Data Mining» more  SDM 2009»
    Parallel Pairwise Clustering.
    16 years 1 months ago
    Parallel Pairwise Clustering.
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    Given the pairwise affinity relations associated with a set of data items, the goal of a clustering algorithm is to automatically partition the data into a small number of homogen...
    Elad Yom-Tov, Noam Slonim
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