Browsing by Subject "Literary analysis"

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    Automatic categorization of ottoman literary texts by poet and time period
    (Springer, London, 2012) Can, Ethem F.; Can, Fazlı; Duygulu, Pınar; Kalpaklı, Mehmet
    Millions of manuscripts and printed texts are available in the Ottoman language. The automatic categorization of Ottoman texts would make these documents much more accessible in various applications ranging from historical investigations to literary analyses. In this work, we use transcribed version of Ottoman literary texts in the Latin alphabet and show that it is possible to develop effective Automatic Text Categorization techniques that can be applied to the Ottoman language. For this purpose, we use two fundamentally different machine learning methods: Naïve Bayes and Support Vector Machines, and employ four style markers: most frequent words, token lengths, two-word collocations, and type lengths. In the experiments, we use the collected works (divans) of ten different poets: two poets from five different hundred-year periods ranging from the 15th to 19th century. The experimental results show that it is possible to obtain highly accurate classifications in terms of poet and time period. By using statistical analysis we are able to recommend which style marker and machine learning method are to be used in future studies. © 2012 Springer-Verlag London Limited.
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    Beyani Tezkiresi önsözü
    (1990) Mustafa, C. Şeyh
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    Paşaların şiirleri
    (1990) Yağmur, S.
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    Redif extraction in handwritten Ottoman literary texts
    (IEEE, 2010) Can, Ethem F.; Duygulu, Pınar; Can, Fazlı; Kalpaklı, Mehmet
    Repeated patterns, rhymes and redifs, are among the fundamental building blocks of Ottoman Divan poetry. They provide integrity of a poem by connecting its parts and bring a melody to its voice. In Ottoman literature, poets wrote their works by making use of the rhymes and redifs of previous poems according to the nazire (creative imitation) tradition either to prove their expertise or to show respect towards old masters. Automatic recognition of redifs would provide important data mining opportunities in literary analyses of Ottoman poetry where the majority of it is in handwritten form. In this study, we propose a matching criterion and method, Redif Extraction using Contour Segments (RECS) using the proposed matching criterion, that detects redifs in handwritten Ottoman literary texts using only visual analysis. Our method provides a success rate of 0.682 in a test collection of 100 poems. © 2010 IEEE.
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