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    SDM
    2004
    SIAM
    189views Data Mining» more  SDM 2004»
    An Abstract Weighting Framework for Clustering Algorithms
    13 years 10 months ago
    An Abstract Weighting Framework for Clustering Algorithms
    Download  www1.univ-ag.fr
    act Weighting Framework for Clustering Algorithms Richard Nock Frank Nielsen Recent works in unsupervised learning have emphasized the need to understand a new trend in algorithmi...
    Richard Nock, Frank Nielsen
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    SDM
    2004
    SIAM
    166views Data Mining» more  SDM 2004»
    A Framework for Discovering Co-Location Patterns in Data Sets with Extended Spatial Objects
    13 years 10 months ago
    A Framework for Discovering Co-Location Patterns in Data Sets with Extended Spatial Objects
    Download  datamining.rutgers.edu
    Hui Xiong, Shashi Shekhar, Yan Huang, Vipin Kumar,...
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    SDM
    2004
    SIAM
    214views Data Mining» more  SDM 2004»
    Making Time-Series Classification More Accurate Using Learned Constraints
    13 years 10 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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    SDM
    2004
    SIAM
    187views Data Mining» more  SDM 2004»
    Class-Specific Ensembles for Active Learning
    13 years 10 months ago
    Class-Specific Ensembles for Active Learning
    Download  www.public.asu.edu
    In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is...
    Amit Mandvikar, Huan Liu
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    SDM
    2004
    SIAM
    207views Data Mining» more  SDM 2004»
    BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint
    13 years 10 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
    218views Data Mining» more  SDM 2004»
    Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
    13 years 10 months ago
    Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
    Download  www.riacs.edu
    This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
    Ashok N. Srivastava
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    SDM
    2004
    SIAM
    187views Data Mining» more  SDM 2004»
    Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data
    13 years 10 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
    2004
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    123views Data Mining» more  SDM 2004»
    Nonlinear Manifold Learning for Data Stream
    13 years 10 months ago
    Nonlinear Manifold Learning for Data Stream
    Download  www.iipl.fudan.edu.cn
    There has been a renewed interest in understanding the structure of high dimensional data set based on manifold learning. Examples include ISOMAP [25], LLE [20] and Laplacian Eige...
    Martin H. C. Law, Nan Zhang 0002, Anil K. Jain
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    SDM
    2004
    SIAM
    194views Data Mining» more  SDM 2004»
    Finding Frequent Patterns in a Large Sparse Graph
    13 years 10 months ago
    Finding Frequent Patterns in a Large Sparse Graph
    Download  glaros.dtc.umn.edu
    Graph-based modeling has emerged as a powerful abstraction capable of capturing in a single and unified framework many of the relational, spatial, topological, and other characteri...
    Michihiro Kuramochi, George Karypis
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    SDM
    2004
    SIAM
    253views Data Mining» more  SDM 2004»
    Density-Connected Subspace Clustering for High-Dimensional Data
    13 years 10 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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