A Comprehensive Methodology for Authorship Attribution of Literary Textual Works
DOI:
https://doi.org/10.31713/MCIT.2025.043Keywords:
authorship attribution, stylometry, machine learning, feature engineering, Azerbaijani languageAbstract
This study presents a comprehensive framework for authorship recognition, specifically tailored for literary works of fiction. There are two peculiarity of the considered problem. First, the problem involves authorship attribution of both large and small literary works. Second, the texts which are available for identification and testing of a recognition model are quite limited, since many writers write only a few literary works throughout their lives. In the study approaches used for addressing the aforementioned issues. Computer experiments were carried out on the Azerbaijani writers example.
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Copyright (c) 2025 Modeling, Control and Information Technologies: Proceedings of International scientific and practical conference

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