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    SDM
    2009
    SIAM
    111views Data Mining» more  SDM 2009»
    A New Constraint for Mining Sets in Sequences.
    14 years 7 months ago
    A New Constraint for Mining Sets in Sequences.
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    Discovering interesting patterns in event sequences is a popular task in the field of data mining. Most existing methods try to do this based on some measure of cohesion to deter...
    Bart Goethals, Boris Cule, Céline Robardet
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    SDM
    2009
    SIAM
    225views Data Mining» more  SDM 2009»
    Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
    14 years 7 months ago
    Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
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    Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
    Fei Wang, Chris H. Q. Ding, Tao Li
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    SDM
    2009
    SIAM
    176views Data Mining» more  SDM 2009»
    Constraint-Based Subspace Clustering.
    14 years 7 months ago
    Constraint-Based Subspace Clustering.
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    In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
    Élisa Fromont, Adriana Prado, Céline...
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    SDM
    2009
    SIAM
    117views Data Mining» more  SDM 2009»
    Spatially Cost-Sensitive Active Learning.
    14 years 7 months ago
    Spatially Cost-Sensitive Active Learning.
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    In active learning, one attempts to maximize classifier performance for a given number of labeled training points by allowing the active learning algorithm to choose which points...
    Alexander Liu, Goo Jun, Joydeep Ghosh
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    SDM
    2009
    SIAM
    164views Data Mining» more  SDM 2009»
    Time-Decayed Correlated Aggregates over Data Streams.
    14 years 7 months ago
    Time-Decayed Correlated Aggregates over Data Streams.
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    Data stream analysis frequently relies on identifying correlations and posing conditional queries on the data after it has been seen. Correlated aggregates form an important examp...
    Graham Cormode, Srikanta Tirthapura, Bojian Xu
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