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    SDM
    2009
    SIAM
    157views Data Mining» more  SDM 2009»
    MUSK: Uniform Sampling of k Maximal Patterns.
    16 years 3 months ago
    MUSK: Uniform Sampling of k Maximal Patterns.
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    Recent research in frequent pattern mining (FPM) has shifted from obtaining the complete set of frequent patterns to generating only a representative (summary) subset of frequent ...
    Mohammad Al Hasan, Mohammed Javeed Zaki
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    SDM
    2009
    SIAM
    235views Data Mining» more  SDM 2009»
    Topic Cube: Topic Modeling for OLAP on Multidimensional Text Databases.
    16 years 3 months ago
    Topic Cube: Topic Modeling for OLAP on Multidimensional Text Databases.
    Download  www.cs.uiuc.edu
    As the amount of textual information grows explosively in various kinds of business systems, it becomes more and more desirable to analyze both structured data records and unstruc...
    ChengXiang Zhai, Duo Zhang, Jiawei Han
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    SDM
    2009
    SIAM
    394views Data Mining» more  SDM 2009»
    Multi-Modal Hierarchical Dirichlet Process Model for Predicting Image Annotation and Image-Object Label Correspondence.
    16 years 3 months ago
    Multi-Modal Hierarchical Dirichlet Process Model for Predicting Image Annotation and Image-Object Label Correspondence.
    Download  www.cs.iastate.edu
    Many real-world applications call for learning predictive relationships from multi-modal data. In particular, in multi-media and web applications, given a dataset of images and th...
    Oksana Yakhnenko, Vasant Honavar
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    SDM
    2009
    SIAM
    219views Data Mining» more  SDM 2009»
    A Hybrid Data Mining Metaheuristic for the p-Median Problem.
    16 years 3 months ago
    A Hybrid Data Mining Metaheuristic for the p-Median Problem.
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    Metaheuristics represent an important class of techniques to solve, approximately, hard combinatorial optimization problems for which the use of exact methods is impractical. In t...
    Alexandre Plastino, Erick R. Fonseca, Richard Fuch...
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    ECIR
    2009
    Springer
    114views Information Technology» more  ECIR 2009»
    Correlation of Term Count and Document Frequency for Google N-Grams
    16 years 3 months ago
    Correlation of Term Count and Document Frequency for Google N-Grams
    Download  www.cs.odu.edu
    For bounded datasets such as the TREC Web Track (WT10g) the computation of term frequency (TF) and inverse document frequency (IDF) is not difficult. However, when the corpus is th...
    Martin Klein, Michael L. Nelson
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