Elena Tutubalina
Title
Cited by
Cited by
Year
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
712015
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
452017
A large-scale COVID-19 Twitter chatter dataset for open scientific research--an international collaboration
JM Banda, R Tekumalla, G Wang, J Yu, T Liu, Y Ding, E Artemova, ...
arXiv preprint arXiv:2004.03688, 2020
442020
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
432018
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
34*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
25*2017
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
232019
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
222017
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
212015
Overview of the fifth social media mining for health applications (# smm4h) shared tasks at coling 2020
A Klein, I Alimova, I Flores, A Magge, Z Miftahutdinov, AL Minard, ...
Proceedings of the Fifth Social Media Mining for Health Applications, 2020
172020
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
162020
KFU NLP team at SMM4H 2019 tasks: Want to extract adverse drugs reactions from tweets? BERT to the rescue
Z Miftahutdinov, I Alimova, E Tutubalina
Proceedings of the fourth social media mining for health applications, 2019
132019
Inferring sentiment-based priors in topic models
E Tutubalina, S Nikolenko
Mexican International Conference on Artificial Intelligence, 92-104, 2015
132015
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
112017
Target-based topic model for problem phrase extraction
E Tutubalina
European Conference on Information Retrieval, 271-277, 2015
112015
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
102018
Automated prediction of demographic information from medical user reviews
E Tutubalina, S Nikolenko
International Conference on Mining Intelligence and Knowledge Exploration, 2016
102016
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
102014
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
92014
AspeRa: aspect-based rating prediction model
SI Nikolenko, E Tutubalina, V Malykh, I Shenbin, A Alekseev
European Conference on Information Retrieval, 163-171, 2019
8*2019
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