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    SDM
    2009
    SIAM
    117views Data Mining» more  SDM 2009»
    Spatially Cost-Sensitive Active Learning.
    14 years 8 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
    105views Data Mining» more  SDM 2009»
    Exploiting Semantic Constraints for Estimating Supersenses with CRFs.
    14 years 8 months ago
    Exploiting Semantic Constraints for Estimating Supersenses with CRFs.
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    The annotation of words and phrases by ontology concepts is extremely helpful for semantic interpretation. However many ontologies, e.g. WordNet, are too fine-grained and even hu...
    Gerhard Paaß, Frank Reichartz
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    SDM
    2009
    SIAM
    291views Data Mining» more  SDM 2009»
    Detection and Characterization of Anomalies in Multivariate Time Series.
    14 years 8 months ago
    Detection and Characterization of Anomalies in Multivariate Time Series.
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    Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
    Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...
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    SDM
    2009
    SIAM
    235views Data Mining» more  SDM 2009»
    Topic Cube: Topic Modeling for OLAP on Multidimensional Text Databases.
    14 years 8 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
    215views Data Mining» more  SDM 2009»
    Hybrid Clustering of Text Mining and Bibliometrics Applied to Journal Sets.
    14 years 8 months ago
    Hybrid Clustering of Text Mining and Bibliometrics Applied to Journal Sets.
    Download  www.siam.org
    To obtain correlated and complementary information contained in text mining and bibliometrics, hybrid clustering to incorporate textual content and citation information has become...
    Bart De Moor, Frizo A. L. Janssens, Shi Yu, Wolfga...
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    SDM
    2009
    SIAM
    208views Data Mining» more  SDM 2009»
    Topic Evolution in a Stream of Documents.
    14 years 8 months ago
    Topic Evolution in a Stream of Documents.
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    Document collections evolve over time, new topics emerge and old ones decline. At the same time, the terminology evolves as well. Much literature is devoted to topic evolution in ...
    Alexander Hinneburg, Andrè Gohr, Myra Spili...
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    SDM
    2009
    SIAM
    204views Data Mining» more  SDM 2009»
    Application of Bayesian Partition Models in Warranty Data Analysis.
    14 years 8 months ago
    Application of Bayesian Partition Models in Warranty Data Analysis.
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    Automotive companies are forced to continuously extend and improve their product line-up. However, increasing diversity, higher design complexity, and shorter development cycles c...
    Axel Blumenstock, Christoph Schlieder, Markus M&uu...
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    SDM
    2009
    SIAM
    138views Data Mining» more  SDM 2009»
    The Metric Dilemma: Competence-Conscious Associative Classification.
    14 years 8 months ago
    The Metric Dilemma: Competence-Conscious Associative Classification.
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    Adriano Veloso, Mohammed Javeed Zaki, Wagner Meira...
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    SDM
    2009
    SIAM
    107views Data Mining» more  SDM 2009»
    A Semi-Supervised Framework for Feature Mapping and Multiclass Classification.
    14 years 8 months ago
    A Semi-Supervised Framework for Feature Mapping and Multiclass Classification.
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    Bo Chen, Ivor Tsang, Tak-Lam Wong, Wai Lam
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    SDM
    2009
    SIAM
    193views Data Mining» more  SDM 2009»
    Agglomerative Mean-Shift Clustering via Query Set Compression.
    14 years 8 months ago
    Agglomerative Mean-Shift Clustering via Query Set Compression.
    Download  www.siam.org
    Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets...
    Xiaotong Yuan, Bao-Gang Hu, Ran He
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