Deep transfer learning baselines for sentiment analysis in Russian

Author:

Smetanin Sergey,Komarov MikhailORCID

Publisher

Elsevier BV

Subject

Library and Information Sciences,Management Science and Operations Research,Computer Science Applications,Media Technology,Information Systems

Reference107 articles.

1. Adaskina, Y. V., Panicheva, P., & Popov, A. (2015). Syntax-based sentiment analysis of tweets in Russian. In Computational linguistics and intellectual technologies. Papers from the annual international conference dialogue 2015 (pp. 1–11).

2. Akbik, A., Blythe, D., & Vollgraf, R. (2018). Contextual string embeddings for sequence labeling. In Proceedings of the 27th international conference on computational linguistics COLING (pp. 1638–1649).

3. User profiling in text-based recommender systems based on distributed word representations;Alekseev,2016

4. A machine learning approach to classification of drug reviews in Russian;Alimova,2017

5. Arkhipenko, K., Kozlov, I., Trofimovich, J., Skorniakov, K., Gomzin, A., & Turdakov, D. (2016). Comparison of neural network architectures for sentiment analysis of russian tweets. In Computational linguistics and intellectual technologies. Papers from the annual international conference dialogue 2016 (pp. 50–59).

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