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    SDM
    2009
    SIAM
    176views Data Mining» more  SDM 2009»
    Constraint-Based Subspace Clustering.
    14 years 1 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
    112views Data Mining» more  SDM 2009»
    A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning.
    14 years 1 months ago
    A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning.
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    Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluat...
    Frederik Janssen, Johannes Fürnkranz
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    SDM
    2009
    SIAM
    161views Data Mining» more  SDM 2009»
    Polynomial-Delay and Polynomial-Space Algorithms for Mining Closed Sequences, Graphs, and Pictures in Accessible Set Systems.
    14 years 1 months ago
    Polynomial-Delay and Polynomial-Space Algorithms for Mining Closed Sequences, Graphs, and Pictures in Accessible Set Systems.
    Download  www-ikn.ist.hokudai.ac.jp
    In this paper, we study efficient closed pattern mining in a general framework of set systems, which are families of subsets ordered by set-inclusion with a certain structure, pro...
    Hiroki Arimura, Takeaki Uno
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    SDM
    2009
    SIAM
    157views Data Mining» more  SDM 2009»
    MUSK: Uniform Sampling of k Maximal Patterns.
    14 years 1 months ago
    MUSK: Uniform Sampling of k Maximal Patterns.
    Download  www.siam.org
    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
    114views Data Mining» more  SDM 2009»
    On the Comparison of Relative Clustering Validity Criteria.
    14 years 1 months ago
    On the Comparison of Relative Clustering Validity Criteria.
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    Many different relative clustering validity criteria exist that are very useful in practice as quantitative measures for evaluating the quality of data partitions, and new criter...
    Lucas Vendramin, Ricardo J. G. B. Campello, Eduard...
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    SDM
    2009
    SIAM
    179views Data Mining» more  SDM 2009»
    Parallel Large Scale Feature Selection for Logistic Regression.
    14 years 1 months ago
    Parallel Large Scale Feature Selection for Logistic Regression.
    Download  www.cs.umass.edu
    Daria Sorokina, Jeremy Kubica, Sameer Singh, Scott...
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    SDM
    2009
    SIAM
    196views Data Mining» more  SDM 2009»
    MultiVis: Content-Based Social Network Exploration through Multi-way Visual Analysis.
    14 years 1 months ago
    MultiVis: Content-Based Social Network Exploration through Multi-way Visual Analysis.
    Download  www.siam.org
    With the explosion of social media, scalability becomes a key challenge. There are two main aspects of the problems that arise: 1) data volume: how to manage and analyze huge data...
    Ching-Yung Lin, Jimeng Sun, Nan Cao, Shixia Liu, S...
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    SDM
    2009
    SIAM
    152views Data Mining» more  SDM 2009»
    Multiple Kernel Clustering.
    14 years 1 months ago
    Multiple Kernel Clustering.
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    Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
    Bin Zhao, James T. Kwok, Changshui Zhang
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    SDM
    2009
    SIAM
    144views Data Mining» more  SDM 2009»
    CORE: Nonparametric Clustering of Large Numeric Databases.
    14 years 1 months ago
    CORE: Nonparametric Clustering of Large Numeric Databases.
    Download  www.siam.org
    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
    175views Data Mining» more  SDM 2009»
    Low-Entropy Set Selection.
    14 years 1 months ago
    Low-Entropy Set Selection.
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    Most pattern discovery algorithms easily generate very large numbers of patterns, making the results impossible to understand and hard to use. Recently, the problem of instead sel...
    Hannes Heikinheimo, Jilles Vreeken, Arno Siebes, H...
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