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      Automatic categorization of Ottoman poems

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      Author
      Can, E. F.
      Can, F.
      Duygulu, P.
      Kalpakli, M.
      Date
      2014
      Source Title
      Glottotheory: international journal of theoretical linguistics
      Print ISSN
      1337-7892
      Electronic ISSN
      2196-6907
      Publisher
      De Gruyter Akademie Forschung
      Volume
      4
      Issue
      2
      Pages
      1 - 15
      Language
      English
      Type
      Article
      Item Usage Stats
      142
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      98
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      Abstract
      Authorship attribution and identifying time period of literary works are fundamental problems in quantitative analysis of languages. We investigate two fundamentally different machine learning text categorization methods, Support Vector Machines (SVM) and Naïve Bayes (NB), and several style markers in the categorization of Ottoman poems according to their poets and time periods. We use the collected works (divans) of ten different Ottoman poets: two poets from each of the five different hundred-year periods ranging from the 15th to 19 th century. Our experimental evaluation and statistical assessments show that it is possible to obtain highly accurate and reliable classifications and to distinguish the methods and style markers in terms of their effectiveness.
      Keywords
      Ottoman poems
      Authorship attribution
      Automatic text categorization
      Historical literary texts
      Ottoman
      Permalink
      http://hdl.handle.net/11693/13047
      Published Version (Please cite this version)
      http://dx.doi.org/10.1524/glot.2013.0014
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      • Department of Computer Engineering 1422
      • Department of History 262
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