1 Ocak 2013 Konferans bildirisi Açık Erişim

Ozalp, Nuri; Aykanat, Sinem; Erdem, Zeki; Ayan, Ugur

Dublin Core

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  <dc:creator>Ozalp, Nuri</dc:creator>
  <dc:creator>Aykanat, Sinem</dc:creator>
  <dc:creator>Erdem, Zeki</dc:creator>
  <dc:creator>Ayan, Ugur</dc:creator>
  <dc:date>2013-01-01</dc:date>
  <dc:description>Author detection is a challenging problem for articles on the Internet (forums, blogs, etc.) due to lack of substantial content. Therefore, author detection for these articles is much more difficult than books, reports and other documents. In this study, the authors of newspaper articles are categorized. We tried to detect authors of articles of test data by using frequently used words in these categories. In doing so, we applied the improved Naive Bayesian machine learning algorithm.</dc:description>
  <dc:identifier>https://aperta.ulakbim.gov.trrecord/91537</dc:identifier>
  <dc:identifier>oai:zenodo.org:91537</dc:identifier>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://www.opendefinition.org/licenses/cc-by</dc:rights>
  <dc:title>Improved Naive Bayesian Algorithm for Author Detection</dc:title>
  <dc:type>info:eu-repo/semantics/conferencePaper</dc:type>
  <dc:type>publication-conferencepaper</dc:type>
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