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    KDD
    2000
    ACM
    149views Data Mining» more  KDD 2000»
    Efficient clustering of high-dimensional data sets with application to reference matching
    13 years 11 months ago
    Efficient clustering of high-dimensional data sets with application to reference matching
    Download  www.kamalnigam.com
    Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
    Andrew McCallum, Kamal Nigam, Lyle H. Ungar
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    FLAIRS
    2010
    389views Artificial Intelligence» more  FLAIRS 2010»
    Using a Graph-Based Approach for Discovering Cybercrime
    13 years 10 months ago
    Using a Graph-Based Approach for Discovering Cybercrime
    Download  www.eecs.wsu.edu
    The ability to mine data represented as a graph has become important in several domains for detecting various structural patterns. One important area of data mining is anomaly det...
    William Eberle, Lawrence B. Holder, Jeffrey Graves
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    SDM
    2007
    SIAM
    89views Data Mining» more  SDM 2007»
    Preventing Information Leaks in Email
    13 years 9 months ago
    Preventing Information Leaks in Email
    Download  www.cs.cmu.edu
    The widespread use of email has raised serious privacy concerns. A critical issue is how to prevent email information leaks, i.e., when a message is accidentally addressed to non-...
    Vitor R. Carvalho, William W. Cohen
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    SDM
    2007
    SIAM
    98views Data Mining» more  SDM 2007»
    Lattice based Clustering of Temporal Gene-Expression Matrices
    13 years 9 months ago
    Lattice based Clustering of Temporal Gene-Expression Matrices
    Download  siam.org
    Individuals show different cell classes when they are in the different stages of a disease, have different disease subtypes, or have different response to a treatment or envir...
    Yang Huang, Martin Farach-Colton
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    SDM
    2003
    SIAM
    184views Data Mining» more  SDM 2003»
    Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
    13 years 9 months ago
    Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
    Download  www-users.cs.umn.edu
    The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
    Levent Ertöz, Michael Steinbach, Vipin Kumar
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