Elena Tutubalina
Cited by
Cited by
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
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
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
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
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
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
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
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
Inferring sentiment-based priors in topic models
E Tutubalina, S Nikolenko
Mexican International Conference on Artificial Intelligence, 92-104, 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
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
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
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
Automated prediction of demographic information from medical user reviews
E Tutubalina, S Nikolenko
International Conference on Mining Intelligence and Knowledge Exploration, 2016
Target-based topic model for problem phrase extraction
E Tutubalina
European Conference on Information Retrieval, 271-277, 2015
Demographic prediction based on user reviews about medications
E Tutubalina, S Nikolenko
Computación y Sistemas 21 (2), 227-241, 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
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
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
Distant supervision for sentiment attitude extraction
N Rusnachenko, N Loukachevitch, E Tutubalina
Proceedings of the International Conference on Recent Advances in Natural, 2019
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