Automatic Extraction of Lithuanian Cybersecurity Terms Using Deep Learning Approaches
| Autor: | Aivaras Rokas, Sigita Rackevičienė, Andrius Utka |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
cybersecurity
business.industry Computer science Deep learning Extraction (chemistry) deep learning Lithuanian neural networks computer.software_genre language.human_language automatic term extraction terminology language Artificial intelligence business embeddings computer Natural language processing |
| Zdroj: | Baltic HLT |
| Popis: | The paper presents the results of research on deep learning methods aiming to determine the most effective one for automatic extraction of Lithuanian terms from a specialized domain (cybersecurity) with very restricted resources. A semi-supervised approach to deep learning was chosen for the research as Lithuanian is a less resourced language and large amounts of data, necessary for unsupervised methods, are not available in the selected domain. The findings of the research show that Bi-LSTM network with Bidirectional Encoder Representations from Transformers (BERT) can achieve close to state-of-the-art results. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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