Natural Language Processing Based Poet Recognition with Supervised Learning on Turkish Poetry Dataset

Abstract

Natural language processing-based studies become popular nowadays and Turkish based studies are increasing. The problem of author classification is based on determining whether an anonymous text belongs to one of the popular authors. This research problem is motivated by the idea that each author's work will reflect some basic features about the author's intellectual vocabulary and thus it should be possible to distinguish between authors. In this study, 50 poems of 5 different poets from Turkish Literature were taken and a dataset was obtained. Experiments were performed on the dataset using 9 different classifier methods. This is a preliminary study that will serve as a basis for future studies.