Abstract
The paper presents the results of applying the BERT representation model in the named entity recognition task for the cybersecurity domain in Russian. Several variants of the model were investigated. The best results were obtained using the BERT model, trained on the target collection of information security texts. We also explored a new form of data augmentation for the task of named entity recognition.
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CITATION STYLE
Tikhomirov, M., Loukachevitch, N., Sirotina, A., & Dobrov, B. (2020). Using bert and augmentation in named entity recognition for cybersecurity domain. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12089 LNCS, pp. 16–24). Springer. https://doi.org/10.1007/978-3-030-51310-8_2
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