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    JIS
    2007
    91views more  JIS 2007»
    Clustering methodologies for identifying country core competencies
    13 years 4 months ago
    Clustering methodologies for identifying country core competencies
    Download  static.msi.umn.edu
    is.sagepub.com/cgi/content/abstract/33/1/21 The online version of this article can be found at: Published by: http://www.sagepublications.com On behalf of: Chartered Institute of L...
    Ronald N. Kostoff, J. Antonio del Río, H&ea...
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    CLUSTER
    2006
    IEEE
    152views Distributed And Parallel Com...» more  CLUSTER 2006»
    A Performance Prediction Methodology for Data-dependent Parallel Applications
    13 years 11 months ago
    A Performance Prediction Methodology for Data-dependent Parallel Applications
    Download  www.cvc.uab.es
    The increase in the use of parallel distributed architectures in order to solve large-scale scientific problems has generated the need for performance prediction for both determi...
    Paula Cecilia Fritzsche, Concepció Roig, An...
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    DKE
    2007
    115views more  DKE 2007»
    An improved methodology on information distillation by mining program source code
    13 years 4 months ago
    An improved methodology on information distillation by mining program source code
    Download  www.cs.man.ac.uk
    This paper presents a methodology for knowledge acquisition from source code. We use data mining to support semiautomated software maintenance and comprehension and provide practi...
    Yiannis Kanellopoulos, Christos Makris, Christos T...
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    ENGL
    2007
    92views more  ENGL 2007»
    K-Mutual Nearest Neighbour Approach for Clustering Two-Dimensional Shapes Described by Fuzzy-Symbolic Features
    13 years 4 months ago
    K-Mutual Nearest Neighbour Approach for Clustering Two-Dimensional Shapes Described by Fuzzy-Symbolic Features
    Download  www.engineeringletters.com
    Abstract— In this paper, a new method of representing twodimensional shapes using fuzzy-symbolic features and a similarity measure defined over fuzzy-symbolic features useful for...
    H. S. Nagendraswamy, D. S. Guru
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    IBPRIA
    2003
    Springer
    98views Pattern Recognition» more  IBPRIA 2003»
    Incrementally Assessing Cluster Tendencies with a Maximum Variance Cluster Algorithm
    13 years 10 months ago
    Incrementally Assessing Cluster Tendencies with a Maximum Variance Cluster Algorithm
    Download  www3.ntu.edu.sg
    A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
    Krzysztof Rzadca, Francesc J. Ferri
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