Automatic categorization of Ottoman poems

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.