@electronic{www.r-bloggers.com,
   title       = {Julia, I Love You | (R news & tutorials)}, 
   url         = {http://www.r-bloggers.com/julia-i-love-you/},
   biburl      = {https://puma.uni-kassel.de/url/be555060c87db7b798ce4afa21537e7e/hotho},
   keywords    = {computing fast hadoop language parallel programming rechnen scientific},
   added-at    = {2013-02-01T11:54:59.000+0100},
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}

@electronic{mapbox.com,
   title       = {TileMill | Fast and beautiful maps}, 
   url         = {http://mapbox.com/tilemill/},
   biburl      = {https://puma.uni-kassel.de/url/1383a968f0160a908b8fb9fd6ff1e57d/hotho},
   keywords    = {beautiful fast maps tools web},
   added-at    = {2012-06-23T17:52:46.000+0200},
   description = {Design beautiful maps},
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   intrahash   = {1383a968f0160a908b8fb9fd6ff1e57d}
}

@electronic{www.coli.uni-saarland.de,
   title       = {SVectors: Fast implementation of Jiang-Conrath similarity in Python}, 
   url         = {http://www.coli.uni-saarland.de/~hagenf/software/svectors/},
   biburl      = {https://puma.uni-kassel.de/url/1129b7ae821c49ea10452b951d4649d0/benz},
   keywords    = {fast jiang_conrath python semantic_relatedness software},
   added-at    = {2011-02-07T07:26:40.000+0100},
   description = {},
   interhash   = {1129b7ae821c49ea10452b951d4649d0}, 
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@electronic{www.borgelt.net,
   title       = {Apriori (and other) implementations by Christian Borgelt}, 
   url         = {http://www.borgelt.net/fpm.html},
   biburl      = {https://puma.uni-kassel.de/url/7228a89e5e8f7c8bddf3d1f5b550daba/benz},
   keywords    = {algorithm apriori association_rules borgelt c download fast free tool},
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@electronic{www.csie.ntu.edu.tw,
   title       = {LIBLINEAR -- A Library for Large Linear Classification}, 
   url         = {http://www.csie.ntu.edu.tw/~cjlin/liblinear/},
   biburl      = {https://puma.uni-kassel.de/url/f4a33bdb48268acb1db1acc5cdc92f3a/hotho},
   keywords    = {classification fast liblinear library multilabel regression svm tools},
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   description = {LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM.

Main features of LIBLINEAR include

    * Same data format as LIBSVM, our general-purpose SVM solver, and also similar usage
    * Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer
    * Cross validation for model selection
    * Probability estimates (logistic regression only)
    * Weights for unbalanced data
    * MATLAB/Octave, Java interfaces},
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@electronic{hunch.net,
   title       = {Vowpal Wabbit (Fast Online Learning)}, 
   url         = {http://hunch.net/~vw/},
   biburl      = {https://puma.uni-kassel.de/url/02f90c2903e5c429024091fbc6bec0a1/hotho},
   keywords    = {dm fast learning ml online},
   added-at    = {2008-01-01T11:23:02.000+0100},
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@electronic{www.kowari.org,
   title       = {kowari}, 
   url         = {http://www.kowari.org/},
   biburl      = {https://puma.uni-kassel.de/url/36b6fa51543649dd61bc2606f128c13c/hotho},
   keywords    = {web store fast semantic rdf},
   added-at    = {2006-03-06T08:36:50.000+0100},
   description = {Kowari is an Open Source, massively scalable, transaction-safe, purpose-built database for the storage, retrieval and analysis of metadata. Kowari is written in Java and licensed under the Mozilla Public License.},
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   intrahash   = {36b6fa51543649dd61bc2606f128c13c}
}