Automatic categorization of ottoman literary texts by poet and time period
Author
Can, Ethem F.
Can, Fazlı
Duygulu, Pınar
Kalpaklı, Mehmet
Date
2012Source Title
Computer and Information Sciences II
Publisher
Springer, London
Pages
51 - 57
Language
English
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Abstract
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.
Keywords
Automatic categorizationAutomatic text categorization
Highly accurate
Literary analysis
Literary texts
Machine learning methods
Printed texts
Style markers
Biographies
Information science
Text processing
Learning systems
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http://hdl.handle.net/11693/28118Published Version (Please cite this version)
https://doi.org/10.1007/978-1-4471-2155-8_6https://doi.org/10.1007/978-1-4471-2155-8