• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • A
  • A
  • A
  • A
  • A
Обычная версия сайта
  • RU
  • EN
  • HSE University
  • Publications
  • Book chapter
  • Automatic morphological analysis on the material of Russian social media texts
  • RU
  • EN
Расширенный поиск
Высшая школа экономики
Национальный исследовательский университет
Priority areas
  • business informatics
  • economics
  • engineering science
  • humanitarian
  • IT and mathematics
  • law
  • management
  • mathematics
  • sociology
  • state and public administration
by year
  • 2027
  • 2026
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2012
  • 2011
  • 2010
  • 2009
  • 2008
  • 2007
  • 2006
  • 2005
  • 2004
  • 2003
  • 2002
  • 2001
  • 2000
  • 1999
  • 1998
  • 1997
  • 1996
  • 1995
  • 1994
  • 1993
  • 1992
  • 1991
  • 1990
  • 1989
  • 1988
  • 1987
  • 1986
  • 1985
  • 1984
  • 1983
  • 1982
  • 1981
  • 1980
  • 1979
  • 1978
  • 1977
  • 1976
  • 1975
  • 1974
  • 1973
  • 1972
  • 1971
  • 1970
  • 1969
  • 1968
  • 1967
  • 1966
  • 1965
  • 1964
  • 1963
  • 1958
  • More
Subject
News
July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.

 

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!

Publications
  • Books
  • Articles
  • Chapters of books
  • Working papers
  • Report a publication
  • Research at HSE

?

Automatic morphological analysis on the material of Russian social media texts

P. 11–17.
Fenogenova A., Kazorin V., Karpov I., Krylova T.

Automatic morphological analysis is one of the fundamental and significant tasks of NLP (Natural Language Processing). Due to special features of Internet texts, as they can be both normative texts (news, fiction, nonfiction) and less formal texts (such as blogs and texts from social networks), the morphological tagging has become non-trivial and an actual task. In this paper we describe our experiments in tagging of Internet texts presenting our approach based on deep learning. The new social media test set was created, that allows to compare our system with state-of-the-art open source analyzers on the social media texts material.

Language: English
DOI
Keywords: natural language processingneural networksmorphological tagginguniversal dependenciessocial media texts
Publication based on the results of:
Applied network research with big data and new technological advances (2018)

In book

Proceedings of Third Workshop "Computational linguistics and language science"
Wohlgenannt G., von Waldenfels R., Toldova S., Rakhilina E. V., Lyashevskaya O., Loukachevitch N. V., Artemova E. Issue 4. , Manchester: EasyChair, 2019.
Similar publications
Proceedings of the 43rd International Conference on Machine Learning (ICML 2026)
Seul: PMLR, 2026.
Added: June 4, 2026
Transformer-based approaches for lemmatizing abbreviations in Russian texts
Glazkova A., Lyashevskaya O., Morozov D. et al., Journal of Mathematical Sciences 2025 Vol. 546 P. 32–47
This paper addresses the task of lemmatizing abbreviations in the Russian language. Abbreviation lemmatization is particularly challenging, as it involves not only transforming a word into its normal form but also correctly expanding the abbreviation. We explore two approaches to this task, both leveraging large pretrained language models. The first approach is generative, where the ...
Added: March 10, 2026
RuCLEVR: A Russian Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning
Biryukova K., Chelnokova D., Erkenova J. et al., Communications in Computer and Information Science 2024 Vol. 2364 CCIS P. 109 – 121
Added: February 25, 2026
Screen-Cam Imitation Module for Improving Data Hiding Robustness
Dzhanashia K., Aleksandr Fedosov, Oleg Evsutin, Sensors 2025 Vol. 25 No. 23 Article 7726
Using an attack-simulation module is a well-recognized approach to improving the robustness of end-to-end neural-network-based data-hiding schemes. However, most proposed attack simulators are limited in the types of attacks they cover, usually handling only a basic set of digital transformations. Real, in-demand use cases for data-hiding methods may involve modifications that cannot be modeled by ...
Added: November 28, 2025
Understanding the training dynamics of CoLaNET by its simplified model
O.A. Goryunov, Maslennikov O. V., Kiselev M. V. et al., Chaos, Solitons and Fractals 2026 Vol. 203 Article 117663
Training complex, biologically plausible Spiking Neural Networks (SNNs) with local learning rules is a significant challenge for theoretical analysis. Here we address this problem by developing a comprehensive analytical theory for the learning dynamics of CoLaNET, a recently proposed columnar SNN. In particular, we consider a simplified model that captures the core algorithmic logic of ...
Added: November 28, 2025
Смежные права на результаты интеллектуальной деятельности, созданные искусственным интеллектом: философско-правовой анализ замены критерия творчества на критерий инвестиций
Pakshin P., Актуальные проблемы российского права 2025 Т. 20 № 11 С. 11–18
The paper substantiates the necessity of providing legal protection for the results of intellectual works created by artificial intelligence through the mechanism of related rights. It examines ways to reduce legal risks associated with the creation of intellectual property using artificial intelligence technologies and offers a philosophical and legal analysis of the proposed hypothesis, namely, ...
Added: November 27, 2025
2025 International Joint Conference on Neural Networks (IJCNN)
IEEE, 2025.
Added: November 15, 2025
Segmentation of Vertebral Arteries on the MR Images
Prikhodko R., Moshkin A., Romanov A., , in: 2025 International Russian Automation Conference (RusAutoCon).: IEEE, 2025. P. 273–278.
The vertebral arteries are one of the most important sources of blood supply to the brain, therefore any pathological changes in them can be the reason behind serious diseases. Magnetic Resonance Imaging (MRI) allows diagnosticians to examine main arteries, which is exceptionally important for effective diagnosis. However, because of the small size of arteries relative ...
Added: November 6, 2025
Машинное обучение и представление информации: новые возможности цифровых архивов (рецензия на книгу: Artificial Intelligence, Archives and Manuscripts. New Relationships between the Virtual Archive and Its Referent. Edinburgh: University of Edinburgh, 2025
Penskaja E., Имагология и компаративистика 2025 № 23 С. 380–389
The book Artificial Intelligence, Archives and Manuscripts. New Relationships between the Virtual Archive and Its Referent (2025) is presented. This collective monograph discusses both technological and legal, intellectual issues that researchers and archivists face in automated work with manuscript heritage, artificial intelligence and neural networks. ...
Added: October 30, 2025
Free energy of neural network can predict accuracy after pruning
Surkov A., Sergei Koltcov, Ignatenko V. et al., Physica A: Statistical Mechanics and its Applications 2025 Vol. 681 Article 131085
Neural networks are powerful tools capable of achieving state-of-the-art performance across a wide range of tasks; however, their effectiveness often comes at the cost of extremely large numbers of parameters, which can hinder their deployment in resource-constrained environments. To address this issue, various pruning techniques have been proposed to reduce model size and complexity while ...
Added: October 30, 2025
Artificial Neural Networks and Machine Learning. ICANN 2025 International Workshops and Special Sessions: 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9–12, 2025, Proceedings, Part V
Cham: Springer, 2025.
This book constitutes the refereed proceedings of 34th International Workshops which were held in conjunction with the 34th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2025, held in Kaunas, Lithuania, September 9–12, 2025.   The 20 full papers and 8 abstracts included in this workshop volume were carefully reviewed and selected from 42 submissions. ...
Added: September 29, 2025
Rewriting the Rules: LLMs Vs. Traditional ML in University Admissions
Chepikov I., Karpov I., , in: 26th International Conference, AIED 2025, Palermo, Italy, July 22–26, 2025, Proceedings, Part I. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED.: Springer, 2025. P. 352 – 358.
Modern LLM models such as BERT, ChatGPT, DeepSeek have shown great potential in solving various tasks, including text classification, text generation, analysis and summary of documents. In this paper, we show that these models close to classical ML approaches based on decision trees not only in text processing, but also in processing classical tabular data ...
Added: September 4, 2025
Цифровой театр абсурда: могут ли нейросети поставить новую научную проблему перед психологией? Кейс-сравнение ChatGPT и DeepSeek
Хашутогова У. П., Berezner T., Poddiakov A., Новые психологические исследования 2025 № 3 С. 100–125
The rapid advancement of artificial intelligence technologies has drawn increasing attention from psychological researchers. While neural networks are being integrated into nearly all domains of human activity, the boundaries of their applicability remain unclear — particularly regarding the originality and practical value of the content they generate. Proponents advocate for their widespread adoption, whereas skeptics ...
Added: September 4, 2025
Этические аспекты использования искусственного интеллекта в образовании при подготовке обучающимися письменных работ
Поставнева И. В., Dvoinin A., Информация и образование: границы коммуникаций 2025 Т. 25 № 17 С. 58–59
The article discusses ethically correct and incorrect ways of using generative artificial intelligence by students when preparing written works. In this context, the boundaries of ethically acceptable actions with neural networks are outlined. ...
Added: August 19, 2025
Распознавание рукописного текста и интеллектуальный анализ: возможности нейронных технологий (на примере работы с «Дневником» Ф.П. Литке)
Boltunova E., Laptev A., Имагология и компаративистика 2025 № 23 С. 358–379
Added: June 16, 2025
Neuro- vs brain-: диалог искусственного интеллекта и мозга в пространстве нейроарта
Mcvey A. V., Коммуникации. Медиа. Дизайн 2025 Т. 10 № 1 С. 74–112
В статье многосторонне исследуется понятие «нейроарт». Проведен анализ существующих в художественном и медиадискурсах трактовок данного понятия, выявлена двойственная практика его употребления в отношении двух различных направлений современного искусства: 1) художественных практик, связанных с использованием искусственных нейронных сетей, 2) художественных практик, использующих нейротехнологии в качестве выразительных средств. Каждое из направлений проанализировано с учетом своей медиальной специфичности. ...
Added: May 5, 2025
Особенности правового режима интеллектуальной собственности объектов, созданных искусственным интеллектом в медицине
Лебедева Д. А., Труды по интеллектуальной собственности 2025 Т. 53 № 2 С. 111–119
In the modern world, artificial intelligence (AI) technologies are being actively introduced into various fields of activity, including medicine. This makes it possible to automate complex processes, increase their accuracy and efficiency, and opens up new opportunities for the diagnosis, treatment, and prevention of diseases. However, with the development of AI, there is a need ...
Added: April 10, 2025
Forecasting market volatility using AI and ML models
Pshichenko D., Znanstvena misel 2024 No. 96 P. 38–42
The article analyzes the application of artificial intelligence (AI) models for forecasting market volatility (MV). Examples of algorithms such as recurrent neural networks (RNN), long short-term memory (LSTM) networks, and regression methods are studied, demonstrating their effectiveness in processing time series and identifying complex data patterns. The importance of integrating machine learning (ML), as a ...
Added: March 10, 2025
Study of artificial intelligence models for big data analysis in project management
Pshichenko D., International Journal of Humanities and Natural Sciences 2024 Vol. 8-3(95) P. 180–185
This study explores the application of artificial intelligence (AI) and machine learning (ML) models for big data analysis in project management. By leveraging specific ML algorithms such as decision trees, random forests, support vector machines, neural networks, kmeans clustering, gradient boosting, and natural language processing, project management practices are significantly enhanced. These technologies improve decision-making, ...
Added: March 10, 2025
Роль искусственного интеллекта в управлении кризисными ситуациями в экономике
Pshichenko D., Тенденции развития науки и образования 2024 № 112(3) С. 117–122
The article examines the role of artificial intelligence (AI) in managing crisis situations in the economy. Various AI technologies for forecasting economic shocks and minimizing their consequences are analyzed. Examples of successful AI applications in various sectors are studied. It is emphasized that the use of AI significantly enhances the resilience and adaptability of economic ...
Added: March 10, 2025
  • About
  • About
  • Key Figures & Facts
  • Sustainability at HSE University
  • Faculties & Departments
  • International Partnerships
  • Faculty & Staff
  • HSE Buildings
  • HSE University for Persons with Disabilities
  • Public Enquiries
  • Studies
  • Admissions
  • Programme Catalogue
  • Undergraduate
  • Graduate
  • Exchange Programmes
  • Summer University
  • Summer Schools
  • Semester in Moscow
  • Business Internship
  • Research
  • International Laboratories
  • Research Centres
  • Research Projects
  • Monitoring Studies
  • Conferences & Seminars
  • Academic Jobs
  • Yasin (April) International Academic Conference on Economic and Social Development
  • Media & Resources
  • Publications by staff
  • HSE Journals
  • Publishing House
  • iq.hse.ru: commentary by HSE experts
  • Library
  • Economic & Social Data Archive
  • Video
  • HSE Repository of Socio-Economic Information
  • HSE1993–2026
  • Contacts
  • Copyright
  • Privacy Policy
  • Site Map
Edit