Automatic categorization of ottoman literary texts by poet and time period

Date
2012
Advisor
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Source Title
Computer and Information Sciences II
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Publisher
Springer, London
Volume
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Pages
51 - 57
Language
English
Type
Conference Paper
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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.

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Keywords
Automatic categorization, Automatic 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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