Труды КНЦ вып.12 (ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ вып. 5/2021(12))

9. Wu X. et al. Conditional BERT Contextual Augmentation. Computational Science - ICCS 2019 Lecture Notes in Computer Science. Springer International Publishing, 2019, pp. 84-95. 10.Kang M., Lee K., Lee Y. Filtered BERT: Similarity Filter-Based Augmentation with Bidirectional Transfer Learning for Protected Health Information Prediction in Clinical Documents. Appl. Sci. 2021, Vol. 11, pp. 3668. 11.Zhang J. et al. Enhancing HMM-based biomedical named entity recognition by studying special phenomena. J. Biomed. Inform. 2004, Vol. 37, No 6, pp. 411-422. 12.Sohrab M. G., Miwa M. Deep Exhaustive Model for Nested Named Entity Recognition. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Brussels, Belgium: Association for Computational Linguistics, 2018, pp. 2843-2849. 13.Ju M., Miwa M., Ananiadou S. A Neural Layered Model for Nested Named Entity Recognition. Proceedings of NAACL-HLT 2018, 2018, pp. 1446-1459. 14.Chen Y. et al. A Boundary Regression Model for Nested Named Entity Recognition. ArXiv201114330 Cs, 2020. 15.Dadas S., Protasiewicz J. A Bidirectional Iterative Algorithm for Nested Named Entity Recognition. IEEE Access, 2020, Vol. 8, pp. 135091-135102. 16.Shibuya T., Hovy E. Nested Named Entity Recognition via Second-best Sequence Learning and Decoding. Trans. Assoc. Comput. Linguist, 2020. Vol. 8, pp. 605-620. 17.Huang Z. et al. Iterative viterbi A* algorithm for K-best sequential decoding. 50th Annual Meeting of the Association for Computational Linguistics, ACL 2012 - Proceedings of the Conference, 2012, pp. 611-619. 18.Russian spaCy Models Documentation. Available at: https://spacy.io/models/ ru#ru_core_news_sm 19.Pre-trained embeddings - DeepPavlov 0.15.0 documentation. Available at: http://docs.deeppavlov.ai/en/master/features/pretrained_vectors.html#bert 20.News dataset from Lenta.Ru. Available at: https://kaggle.com/yutkin/corpus-of- russian-news-articles-from-lenta Сведения об авторах П. А. Ломов— кандидат технических наук, старший научный сотрудник ИИММ КНЦ РАН; М. Л. Малоземова — инженер-исследователь ИИММ КНЦ РАН. Information about the authors P. A. Lomov — Candidate o f Science (Tech.), Senior Research Fellow o f the Institute fo r Informatics and Mathematical Modeling Kola Science Centre o f the Russian Academy o f Sciences; M. L. Malozemova — research engineer o f the Institute fo r Informatics and Mathematical Modeling Kola Science Centre o f the Russian Academy o f Sciences. Статья поступила в редакцию 15.11.2021; одобрена после рецензирования 20.11.2021; принята к публикации 08.12.2021. The article was submitted 15.11.2021; approved after reviewing 20.11.2021; accepted fo r publication 08.12.2021. 34