Machine Learning and Philology: An Overview of Methods and Applications

Author:

Gryaznova EkaterinaORCID,Kirina MargaritaORCID,Mikhailova PolinaORCID,Zarembo ValeriaORCID,Moskvina AnnaORCID

Publisher

Springer Nature Switzerland

Reference41 articles.

1. Aggarwal, C.C.: Machine Learning for Text. Springer, Cham (2018)

2. Mahmoudi, M.R., Abbasalizadeh, A.: How statistics and text mining can be applied to literary studies? Digit. Scholars. Human. 34(3), 536–541 (2019)

3. Uglanova, I., Gius, E.: The order of things. A study on topic modelling of literary texts. In: Proceedings of the CHR 2020: Workshop on Computational Humanities Research, CEUR Workshop Proceedings (2020) Available at: http://ceur-ws.org/Vol-2723/long7.pdf

4. Martynenko, G.Y., Sherstinova, T.Y., Melnik, A.G., Popova, T.I.: Methodological issues related with the compilation of digital anthology of Russian short stories (the first third of the 20th century). In: Proceedings of the XXI International United Conference ‘The Internet and Modern Society’, IMS–2018, Computational Linguistics and Computational Ontologies, vol. 2, pp. 99–104. ITMO University, St. Petersburg (2018)

5. Martynenko, G., Sherstinova, T.: Linguistic and stylistic parameters for the study of literary language in the corpus of Russian short stories of the first third of the 20th century. In: R. Piotrowski’s readings in language engineering and applied linguistics, Proceedings of the III International Conference on Language Engineering and Applied Linguistics (PRLEAL-2019), Saint Petersburg, Russia, November 27, 2019, vol. 2552, pp. 105–120. CEUR Workshop Proceedings (2020)

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