| SentiRuEval: testing object-oriented sentiment analysis systems in Russian N Loukachevitch, P Blinov, E Kotelnikov, Y Rubtsova, V Ivanov, ... Proceedings of International Conference Dialog 2, 3-13, 2015 | 65 | 2015 |
| Combination of Deep Recurrent Neural Networks and Conditional Random Fields for Extracting Adverse Drug Reactions from User Reviews E Tutubalina, S Nikolenko Journal of Healthcare Engineering, 1-9, 2017 | 37 | 2017 |
| Medical concept normalization in social media posts with recurrent neural networks E Tutubalina, Z Miftahutdinov, S Nikolenko, V Malykh Journal of biomedical informatics 84, 93-102, 2018 | 29 | 2018 |
| Identifying disease-related expressions in reviews using conditional random fields Z Miftahutdinov, A Tropsha, E Tutubalina Computational Linguistics and Intellectual Technologies: Papers from the …, 2017 | 29* | 2017 |
| Kfu at clef ehealth 2017 task 1: Icd-10 coding of english death certificates with recurrent neural networks Z Miftakhutdinov, E Tutubalina CEUR Workshop Proceedings, 2017 | 21* | 2017 |
| Extracting aspects, sentiment and categories of aspects in user reviews about restaurants and cars VV Ivanov, EV Tutubalina, NR Mingazov, IS Alimova Komp'juternaja Lingvistika i Intellektual'nye Tehnologii, 22-33, 2015 | 21 | 2015 |
| Automated detection of adverse drug reactions from social media posts with machine learning I Alimova, E Tutubalina International Conference on Analysis of Images, Social Networks and Texts, 3-15, 2017 | 17 | 2017 |
| Exploring convolutional neural networks and topic models for user profiling from drug reviews E Tutubalina, S Nikolenko Multimedia Tools and Applications 77 (4), 4791-4809, 2018 | 10 | 2018 |
| Inferring sentiment-based priors in topic models E Tutubalina, S Nikolenko Mexican International Conference on Artificial Intelligence, 92-104, 2015 | 10 | 2015 |
| Unsupervised approach to extracting problem phrases from user reviews of products E Tutubalina, V Ivanov Proceedings of the First AHA!-Workshop on Information Discovery in Text, 48-53, 2014 | 10 | 2014 |
| Clause-based approach to extracting problem phrases from user reviews of products V Ivanov, E Tutubalina International Conference on Analysis of Images, Social Networks and Texts …, 2014 | 10 | 2014 |
| Deep Neural Models for Medical Concept Normalization in User-Generated Texts Z Miftahutdinov, E Tutubalina Proceedings of the 57th Conference of the Association for Computational …, 2019 | 9 | 2019 |
| Using semantic analysis of texts for the identification of drugs with similar therapeutic effects EV Tutubalina, ZS Miftahutdinov, RI Nugmanov, TI Madzhidov, ... Russian Chemical Bulletin 66 (11), 2180-2189, 2017 | 9 | 2017 |
| Automated prediction of demographic information from medical user reviews E Tutubalina, S Nikolenko International Conference on Mining Intelligence and Knowledge Exploration …, 2016 | 9 | 2016 |
| Target-based topic model for problem phrase extraction E Tutubalina European Conference on Information Retrieval, 271-277, 2015 | 9 | 2015 |
| Demographic prediction based on user reviews about medications E Tutubalina, S Nikolenko Computación y Sistemas 21 (2), 227-241, 2017 | 8 | 2017 |
| AspeRa: aspect-based rating prediction model SI Nikolenko, E Tutubalina, V Malykh, I Shenbin, A Alekseev European Conference on Information Retrieval, 163-171, 2019 | 7* | 2019 |
| RecVAE: A New Variational Autoencoder for Top-N Recommendations with Implicit Feedback I Shenbin, A Alekseev, E Tutubalina, V Malykh, SI Nikolenko Proceedings of the 13th International Conference on Web Search and Data …, 2020 | 6 | 2020 |
| A Machine learning approach to classification of drug reviews in Russian I Alimova, E Tutubalina, J Alferova, G Gafiyatullina 2017 Ivannikov ISPRAS Open Conference (ISPRAS), 64-69, 2017 | 6 | 2017 |
| Distant supervision for sentiment attitude extraction N Rusnachenko, N Loukachevitch, E Tutubalina Proceedings of the International Conference on Recent Advances in Natural …, 2019 | 5 | 2019 |
Sergey NikolenkoSteklov Institute of Mathematics at St. Petersburg, RussiaVerified email at logic.pdmi.ras.ru
