<rdf:RDF xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:cc="http://web.resource.org/cc/" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"><channel rdf:about="http://www.bibsonomy.org/user/jil"><title>BibSonomy publications for /user/jil</title><link>http://www.bibsonomy.org/publrss/user/jil</link><description>BibSonomy RSS Feed for /user/jil</description><items><rdf:Seq><rdf:li rdf:resource="http://www.bibsonomy.org/bibtex/2dfa99d567392038673882c932153053c/jil"/><rdf:li rdf:resource="http://www.bibsonomy.org/bibtex/2e46f97a70e986c33b1822d6a247dd1a5/jil"/><rdf:li rdf:resource="http://www.bibsonomy.org/bibtex/2b8f819dc681e76ee9723c72a859dff3c/jil"/><rdf:li rdf:resource="http://www.bibsonomy.org/bibtex/22896eb9538a6ee34f8e6c6757bdcf99e/jil"/><rdf:li rdf:resource="http://www.bibsonomy.org/bibtex/2fa46d1cc0dd56ab40a7f722e569a1fd3/jil"/><rdf:li rdf:resource="http://www.bibsonomy.org/bibtex/2e290abb350b7aa09a412c1dddac55cd6/jil"/><rdf:li rdf:resource="http://www.bibsonomy.org/bibtex/2b4e1a9d4635a9fb1f11a947f1ab3618a/jil"/><rdf:li rdf:resource="http://www.bibsonomy.org/bibtex/2b7cf853e8635bd2887e8dea3d9e10ccb/jil"/><rdf:li rdf:resource="http://www.bibsonomy.org/bibtex/2ad2a33b52e690eaf15da04fff7f12755/jil"/><rdf:li rdf:resource="http://www.bibsonomy.org/bibtex/27cf3e7981cac898c1745418db83e0fd6/jil"/></rdf:Seq></items></channel><item rdf:about="http://www.bibsonomy.org/bibtex/2dfa99d567392038673882c932153053c/jil"><title>A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization.</title><link>http://www.bibsonomy.org/bibtex/2dfa99d567392038673882c932153053c/jil</link><dc:creator>jil</dc:creator><dc:date>2008-05-08T19:46:13+02:00</dc:date><dc:subject>bayes estimator laplace probabilistic rocchio tfidf </dc:subject><content:encoded>&lt;span style=&#034;color:#555555;&#034;&gt;Thorsten &lt;a href=&#034;http://www.bibsonomy.org/author/Joachims&#034;&gt;Joachims&lt;/a&gt;  &lt;/span&gt;&lt;em&gt;ICML, &lt;/em&gt;&lt;em&gt;Seite143-151. &lt;/em&gt;&lt;em&gt;Morgan Kaufmann, &lt;/em&gt;(&lt;em&gt;1997&lt;/em&gt;)</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="http://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/estimator"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/laplace"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/probabilistic"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/rocchio"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/tfidf"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.bibsonomy.org/bibtex/2e46f97a70e986c33b1822d6a247dd1a5/jil"><title>Centroid-Based Document Classification: Analysis and Experimental Results.</title><link>http://www.bibsonomy.org/bibtex/2e46f97a70e986c33b1822d6a247dd1a5/jil</link><dc:creator>jil</dc:creator><dc:date>2008-05-08T18:07:32+02:00</dc:date><dc:subject>average classification classifier cos cosinus interpretation klassifikation learning loose machine rocchio similarity simple tight </dc:subject><content:encoded>&lt;span style=&#034;color:#555555;&#034;&gt;Eui-Hong &lt;a href=&#034;http://www.bibsonomy.org/author/Han&#034;&gt;Han&lt;/a&gt;  und George &lt;a href=&#034;http://www.bibsonomy.org/author/Karypis&#034;&gt;Karypis&lt;/a&gt;  &lt;/span&gt;&lt;em&gt;PKDD, &lt;/em&gt;&lt;em&gt;Volume1910vonLecture Notes in Computer Science, &lt;/em&gt;&lt;em&gt;Seite424-431. &lt;/em&gt;&lt;em&gt;Springer, &lt;/em&gt;(&lt;em&gt;2000&lt;/em&gt;)</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="http://www.bibsonomy.org/tag/average"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/classification"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/classifier"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/cos"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/cosinus"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/interpretation"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/klassifikation"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/learning"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/loose"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/machine"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/rocchio"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/similarity"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/simple"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/tight"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.bibsonomy.org/bibtex/2b8f819dc681e76ee9723c72a859dff3c/jil"><title>Effective methods for improving Naive Bayes text classifiers</title><link>http://www.bibsonomy.org/bibtex/2b8f819dc681e76ee9723c72a859dff3c/jil</link><dc:creator>jil</dc:creator><dc:date>2008-05-06T02:13:03+02:00</dc:date><dc:subject>bayes learning length machine multinomial naive normalization </dc:subject><content:encoded>&lt;span style=&#034;color:#555555;&#034;&gt;S. &lt;a href=&#034;http://www.bibsonomy.org/author/Kim&#034;&gt;Kim&lt;/a&gt;  und H. &lt;a href=&#034;http://www.bibsonomy.org/author/Rim&#034;&gt;Rim&lt;/a&gt;  und D. &lt;a href=&#034;http://www.bibsonomy.org/author/Yook&#034;&gt;Yook&lt;/a&gt;  und H. &lt;a href=&#034;http://www.bibsonomy.org/author/Lim&#034;&gt;Lim&lt;/a&gt;  &lt;/span&gt;(&lt;em&gt;2002&lt;/em&gt;)</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="http://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/learning"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/length"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/machine"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/multinomial"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/naive"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/normalization"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.bibsonomy.org/bibtex/22896eb9538a6ee34f8e6c6757bdcf99e/jil"><title>Improving Multi-class Text Classification with Naive Bayes</title><link>http://www.bibsonomy.org/bibtex/22896eb9538a6ee34f8e6c6757bdcf99e/jil</link><dc:creator>jil</dc:creator><dc:date>2008-05-05T19:34:57+02:00</dc:date><dc:subject>bayes deduction estimation exhaustive herleitung komplett likelihood map maximum mle multinomial naive prior thesis </dc:subject><content:encoded>&lt;span style=&#034;color:#555555;&#034;&gt;Jason D. M. &lt;a href=&#034;http://www.bibsonomy.org/author/Rennie&#034;&gt;Rennie&lt;/a&gt;  &lt;/span&gt;(&lt;em&gt;2001&lt;/em&gt;)</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="http://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/deduction"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/estimation"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/exhaustive"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/herleitung"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/komplett"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/likelihood"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/map"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/maximum"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/mle"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/multinomial"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/naive"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/prior"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/thesis"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.bibsonomy.org/bibtex/2fa46d1cc0dd56ab40a7f722e569a1fd3/jil"><title>A Comparison of Event Models for Naive Bayes Text Classification</title><link>http://www.bibsonomy.org/bibtex/2fa46d1cc0dd56ab40a7f722e569a1fd3/jil</link><dc:creator>jil</dc:creator><dc:date>2008-05-05T19:02:36+02:00</dc:date><dc:subject>bayes bernoulli classification ereignis event model multinomial naive text vergleich </dc:subject><content:encoded>&lt;span style=&#034;color:#555555;&#034;&gt;Andrew &lt;a href=&#034;http://www.bibsonomy.org/author/McCallum&#034;&gt;McCallum&lt;/a&gt;  und Kamal &lt;a href=&#034;http://www.bibsonomy.org/author/Nigam&#034;&gt;Nigam&lt;/a&gt;  &lt;/span&gt;&lt;em&gt;Learning for Text Categorization: Papers from the 1998 AAAI Workshop, &lt;/em&gt;&lt;em&gt;Seite41--48. &lt;/em&gt;(&lt;em&gt;1998&lt;/em&gt;)</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="http://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/bernoulli"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/classification"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/ereignis"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/event"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/multinomial"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/naive"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/text"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/vergleich"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.bibsonomy.org/bibtex/2e290abb350b7aa09a412c1dddac55cd6/jil"><title>Naive (Bayes) at forty: The independence assumption in information retrieval.</title><link>http://www.bibsonomy.org/bibtex/2e290abb350b7aa09a412c1dddac55cd6/jil</link><dc:creator>jil</dc:creator><dc:date>2008-05-05T18:53:49+02:00</dc:date><dc:subject>bayes forty ir naive overview representation text </dc:subject><content:encoded>&lt;span style=&#034;color:#555555;&#034;&gt;David D. &lt;a href=&#034;http://www.bibsonomy.org/author/Lewis&#034;&gt;Lewis&lt;/a&gt;  &lt;/span&gt;&lt;em&gt;Proceedings of ECML-98, 10th European Conference on Machine Learning, &lt;/em&gt;&lt;em&gt;1398, &lt;/em&gt;&lt;em&gt;Seite4--15. &lt;/em&gt;&lt;em&gt;Chemnitz, DE, &lt;/em&gt;&lt;em&gt;Springer Verlag, Heidelberg, DE, &lt;/em&gt;(&lt;em&gt;1998&lt;/em&gt;)</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="http://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/forty"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/ir"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/naive"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/overview"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/representation"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/text"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.bibsonomy.org/bibtex/2b4e1a9d4635a9fb1f11a947f1ab3618a/jil"><title>Spam Filtering with Naive Bayes -- Which Naive Bayes?</title><link>http://www.bibsonomy.org/bibtex/2b4e1a9d4635a9fb1f11a947f1ab3618a/jil</link><dc:creator>jil</dc:creator><dc:date>2008-05-05T18:50:15+02:00</dc:date><dc:subject>bayes metsis multinomial multivariate naive spam </dc:subject><content:encoded>&lt;span style=&#034;color:#555555;&#034;&gt;Vangelis &lt;a href=&#034;http://www.bibsonomy.org/author/Metsis&#034;&gt;Metsis&lt;/a&gt;  und Ion &lt;a href=&#034;http://www.bibsonomy.org/author/Androutsopoulos&#034;&gt;Androutsopoulos&lt;/a&gt;  und Georgios &lt;a href=&#034;http://www.bibsonomy.org/author/Paliouras&#034;&gt;Paliouras&lt;/a&gt;  &lt;/span&gt;(&lt;em&gt;2006&lt;/em&gt;)</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="http://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/metsis"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/multinomial"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/multivariate"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/naive"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/spam"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.bibsonomy.org/bibtex/2b7cf853e8635bd2887e8dea3d9e10ccb/jil"><title>A Short SVM (Support Vector Machine) Tutorial</title><link>http://www.bibsonomy.org/bibtex/2b7cf853e8635bd2887e8dea3d9e10ccb/jil</link><dc:creator>jil</dc:creator><dc:date>2008-05-04T17:00:45+02:00</dc:date><dc:subject>background kkt lagrange math mathe mathematik svm tutorial </dc:subject><content:encoded>&lt;span style=&#034;color:#555555;&#034;&gt;J.P. &lt;a href=&#034;http://www.bibsonomy.org/author/Lewis&#034;&gt;Lewis&lt;/a&gt;  &lt;/span&gt;&lt;em&gt;CGIT Lab / IMSC, &lt;/em&gt;(&lt;em&gt;2004&lt;/em&gt;)</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="http://www.bibsonomy.org/tag/background"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/kkt"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/lagrange"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/math"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/mathe"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/mathematik"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/svm"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.bibsonomy.org/bibtex/2ad2a33b52e690eaf15da04fff7f12755/jil"><title>A Tutorial on Support Vector Machines for Pattern Recognition</title><link>http://www.bibsonomy.org/bibtex/2ad2a33b52e690eaf15da04fff7f12755/jil</link><dc:creator>jil</dc:creator><dc:date>2008-05-04T16:52:21+02:00</dc:date><dc:subject>burges deduction herleitung kkt lagrange svm tutorial </dc:subject><content:encoded>&lt;span style=&#034;color:#555555;&#034;&gt;Christopher J. C. &lt;a href=&#034;http://www.bibsonomy.org/author/Burges&#034;&gt;Burges&lt;/a&gt;  &lt;/span&gt;&lt;em&gt;Data Mining and Knowledge Discovery&lt;/em&gt;&lt;em&gt;2(2):121-167&lt;/em&gt;(&lt;em&gt;1998&lt;/em&gt;)</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="http://www.bibsonomy.org/tag/burges"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/deduction"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/herleitung"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/kkt"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/lagrange"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/svm"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.bibsonomy.org/bibtex/27cf3e7981cac898c1745418db83e0fd6/jil"><title>Transductive Inference for Text Classification using Support Vector Machines</title><link>http://www.bibsonomy.org/bibtex/27cf3e7981cac898c1745418db83e0fd6/jil</link><dc:creator>jil</dc:creator><dc:date>2008-05-02T15:34:36+02:00</dc:date><dc:subject>svm svmlight transductive </dc:subject><content:encoded>&lt;span style=&#034;color:#555555;&#034;&gt;Thorsten &lt;a href=&#034;http://www.bibsonomy.org/author/Joachims&#034;&gt;Joachims&lt;/a&gt;  &lt;/span&gt;&lt;em&gt;Proceedings of ICML-99, 16th International Conference on Machine Learning, &lt;/em&gt;&lt;em&gt;Seite200--209. &lt;/em&gt;&lt;em&gt;Bled, SL, &lt;/em&gt;&lt;em&gt;Morgan Kaufmann Publishers, San Francisco, US, &lt;/em&gt;(&lt;em&gt;1999&lt;/em&gt;)</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="http://www.bibsonomy.org/tag/svm"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/svmlight"/><rdf:li rdf:resource="http://www.bibsonomy.org/tag/transductive"/></rdf:Bag></taxo:topics></item></rdf:RDF>