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    211views Data Mining» more  SDM 2004»
    Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
    15 years 7 months ago
    Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
    Download  www.dbs.informatik.uni-muenchen.de
    Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
    Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
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    253views Data Mining» more  SDM 2004»
    Density-Connected Subspace Clustering for High-Dimensional Data
    15 years 7 months ago
    Density-Connected Subspace Clustering for High-Dimensional Data
    Download  www.dbs.informatik.uni-muenchen.de
    Several application domains such as molecular biology and geography produce a tremendous amount of data which can no longer be managed without the help of efficient and effective ...
    Peer Kröger, Hans-Peter Kriegel, Karin Kailin...
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    SDM
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    187views Data Mining» more  SDM 2004»
    Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data
    15 years 7 months ago
    Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data
    Download  www.cs.utexas.edu
    Microarray experiments have been extensively used for simultaneously measuring DNA expression levels of thousands of genes in genome research. A key step in the analysis of gene e...
    Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvri...
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    SDM
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    207views Data Mining» more  SDM 2004»
    BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint
    15 years 7 months ago
    BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint
    Download  glaros.dtc.umn.edu
    Previous study has shown that mining frequent patterns with length-decreasing support constraint is very helpful in removing some uninteresting patterns based on the observation t...
    Jianyong Wang, George Karypis
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    SDM
    2004
    SIAM
    214views Data Mining» more  SDM 2004»
    Making Time-Series Classification More Accurate Using Learned Constraints
    15 years 7 months ago
    Making Time-Series Classification More Accurate Using Learned Constraints
    Download  www.cs.ucr.edu
    It has long been known that Dynamic Time Warping (DTW) is superior to Euclidean distance for classification and clustering of time series. However, until lately, most research has...
    Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
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