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Near-Zero-Shot Suggestion Mining with a Little Help from WordNet
P. 23–36.
In this work we explore the constructive side of online reviews: advice, tips, requests, and suggestions that users provide about goods, venues and other items of interest. To reduce training costs and annotation efforts needed to build a classifier for a specific label set, we present and evaluate several entailment-based zero-shot approaches to suggestion classification in a label-fully-unseen fashion. In particular, we introduce the strategy of assigning target class labels to sentences with user intentions, which significantly improves prediction quality. The proposed strategies are evaluated with a comprehensive experimental study that validated our results both quantitatively and qualitatively. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Глазкова А. В., Смаль И. В., Lyashevskaya O. et al., Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика) 2025 Т. 527 С. 146–155
This paper presents a study on the effectiveness of discriminative methods for abbreviation lemmatization in Russian texts. Unlike generative approaches, discriminative models select the optimal lemma from a fixed set of candidates, eliminating the risk of generating grammatically incorrect word forms. For the first time in Russian language processing, we conduct a comprehensive analysis of ...
Added: March 10, 2026
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
Viktor V. Prutyanov, Nikita L. Korolev, Aleksandr Y. Romanov, , in: 2025 International Russian Automation Conference (RusAutoCon).: IEEE, 2025. P. 350–354.
This paper presents a UAV visual localization system that leverages zero-shot deep feature matching to achieve localization in 4 degrees of freedom. The proposed system combines short-term optical flow and long-term map matching techniques, integrated through a Kalman filter for robust measurement fusion. Key contributions include the use of pre-trained deep learning models (SuperPoint, ALIKED, ...
Added: November 6, 2025
Kolmogorova A., Калинин А. А., В кн.: Компьютерная лингвистика и интеллектуальные технологии: по материалам международной конференции «Диалог 2022», выпуск 21Вып. 21.: Изд-во РГГУ, 2022. С. 311–322.
The article summarizes the results of two tasks in machine learning paradigm: the task of classification according
to the criterion of dominating emotion on the data of social networks posts in Russian and the regression task using
the same data. The experiments are conducted on the data set collected from VKontakte social network and consisted
of 3879 posts ...
Added: March 18, 2024
A. V. Belov, E. A. Egorova, Bulletin D. Serikbayev East Kazakhstan Technical University 2023 No. 4 P. 92–102
When conducting scientific and technical expertise, it is necessary to analyze the texts of reports on scientific research work. The analysis is carried out in order to determine whether the research being conducted belongs to the class of scientific research and development work in the field of IT. This article discusses the tasks of binary ...
Added: March 9, 2024
I. K. Kusakin, Fedorets O. V., A. Y. Romanov, Scientific and Technical Information Processing 2023 Vol. 50 No. 3 P. 176–183
This paper discusses modern approaches to natural language processing and the application of machine learning models to the task of classifying short scientific texts in Russian. This study is devoted to the analysis of methods for vectorization of textual information, selection of a model for scientific paper clas- sification, and training of linguistic model BERT ...
Added: November 4, 2023
Alimova I., Tutubalina E., , in: Analysis of Images, Social Networks and Texts. 10th International Conference, AIST 2021, Tbilisi, Georgia, December 16–18, 2021, Revised Selected Papers.: Cham: Springer, 2022. P. 37–44.
Automatic monitoring of adverse drug events (ADEs) or reactions (ADRs) is currently receiving significant attention from the biomedical community. In recent years, user-generated data on social media has become a valuable resource for this task. Neural models have achieved impressive performance on automatic text classification for ADR detection. Yet, training and evaluation of these methods ...
Added: April 10, 2023
Кусакин И. К., Цурупа А. М., Алмакаев А. В. et al., В кн.: НТИ-2022. Научная информация в современном мире: глобальные вызовы и национальные приоритеты : материалы 10-ой научной конференции с международным участием, посвященной 70-летию ВИНИТИ РАН, Москва, 25–26 октября 2022 года.: М.: ВИНИТИ РАН, 2022. С. 103–109.
This work is devoted to the study of approaches for training BERT-based classifiers of scientific articles to implement the application with the adoption of the best models for use in the infrastructure of the VINITI RAS. For this purpose, the BERT linguistic model was trained on a specialized corpus of scientific texts for subsequent use ...
Added: January 31, 2023
Кусакин И. К., Федорец О. В., Romanov A., Научно-техническая информация. Серия 2: Информационные процессы и системы 2022 Т. 12 С. 6–9
This paper discusses modern approaches to natural language processing and appliance of artificial intelligence technologies in the task of classifying scientific texts in Russian. The report contains an analysis of implementations of text vectorization methods, a description of experiments with training various classifier models: from classical machine learning algorithms to neural network transformer architectures. ...
Added: January 31, 2023
Sergey Smetanin, Mathematics 2022 Vol. 10 No. 16 Article 2947
Policymakers and researchers worldwide are interested in measuring the subjective well-being (SWB) of populations. In recent years, new approaches to measuring SWB have begun to appear, using digital traces as the main source of information, and show potential to overcome the shortcomings of traditional survey-based methods. In this paper, we propose the formal model for ...
Added: August 15, 2022
Kharlamov A. A., Kulikov A., , in: Neuroinformatics and Semantic Representations: Theory and Applications.: Cambridge Scholars Publishing, 2020. P. 219–231.
В работе показано использование механизма сравнения семантических сетей текстов в задаче диагностики заболеваний с использованием сигнальных сетей. Выявление степени пересечения семантических сетей текстов позволяет говорить о степени их смыслового подобия. Однородная семантическая сеть как множество узлов, связанных дугами, имеет численные характеристики – частоты появления слов, а также пар слов в тексте, которые перенормируются с использованием ...
Added: December 7, 2021
Kharlamov A. A., , in: Neuroinformatics and Semantic Representations: Theory and Applications.: Cambridge Scholars Publishing, 2020. P. 156–167.
На основе представлений об обработке информации в мозге человека [1] реализована технология автоматической смысловой обработки текстов TextAnalyst, позволяющая выявить ключевые понятия текста в их взаимосвязях, реализовать реферирование текстов и их смысловое сравнение (классификацию). Реализованы продукты, использующие функциональность этой технологии: персональный – TextAnalyst, и библиотека COM модулей – TextAnalyst SDK. ...
Added: December 7, 2021
Burnyshev P., Malykh V., Bout A. et al., , in: Proceedings of the 14th International Conference on Natural Language Generation.: Association for Computational Linguistics, 2021. Ch. 20 P. 201–211.
Sub-tasks of intent classification, such as robustness to distribution shift, adaptation to specific user groups and personalization, out-of-domain detection, require extensive and flexible datasets for experiments and evaluation. As collecting such datasets is time- and labor-consuming, we propose to use text generation methods to gather datasets. The generator should be trained to generate utterances that ...
Added: September 23, 2021
Smetanin S., Komarov M. M., , in: IEEE 23rd Conference on Business Informatics (CBI).: IEEE Computer Society, 2021. P. 65–70.
With the widespread use of online social networks, it is becoming more and more difficult to monitor and analyse all the user-generated content. Toxic speech in online conversations should be treated as a matter with serious social gravity, since it may result in both negative impacts on mental health and violent actions in the physical ...
Added: September 14, 2021
Dmitry Romanov, Kazantsev N., Edgeeva E., , in: Business Process Management: Blockchain and Central and Eastern Europe Forum. BPM 2019Vol. 361.: Springer, 2019. P. 337–341.
This paper studies ‘the order effect’ in decision making based on classification results of 120 000 citizen claims to Moscow Government. We use machine learning methods and derive that with 60% probability the first out of two consequent claims is prioritized. We conclude that this impact must be considered whilst developing artificial intelligence units. ...
Added: October 26, 2020
Kopeykina L., Savchenko A., , in: Proceedings of the VI International conference Information Technology and Nanotechnology. Session Image Processing and Earth Remote Sensing (ITNT-IPERS)Vol. 2665: Information Technology and Nanotechnology. Image Processing and Earth Remote Sensing 2020.: Samara: CEUR Workshop Proceedings, 2020. Ch. 39 P. 171–176.
Nowadays, the photo privacy detection is becoming an acute task due to a wide spread of mobile devices with photos published on social networks. As a photo might contain private or sensitive data, there is an urgent need to accurately determine them and impose restrictions on their processing. In this paper we focus on the ...
Added: October 1, 2020
Byzov A., Социология: методология, методы, математическое моделирование 2019 № 49 С. 131–160
Throughout most of their history, sociologists have sought to study unstructured organic texts: newspaper materials, diaries, memoirs, letters, documents, and, more recently, messages, publications and other texts on various online platforms. This article discusses how modern techniques of text mining can improve classical sociological approaches to the analysis of this type of data. The article ...
Added: December 9, 2019
Malafeev A., Nikolaev K., , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Kazan, Russia, July 17–19, 2019, Revised Selected Papers. Communications in Computer and Information ScienceVol. 1086.: Springer, 2020. P. 154–159.
In this paper, a deep learning method study is conducted to solve a new multiclass text classification problem, identifying user interests by text messages. We used an original dataset of almost 90 thousand forum text messages, labeled for ten interests. We experimented with different modern neural network architectures: recurrent and convolutional, as well as simpler ...
Added: November 7, 2019
Pimonova E., Durandin O., Malafeev A., , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected PapersVol. 11832.: Cham: Springer, 2019. P. 193–204.
This work tackles the problem of modeling author style in Russian. In particular, we solve the task of authorship attribution using the collected dataset of 30 authors, 1506 texts written in the period of 18th – 21st century. We apply various approaches to solving the attribution problem: Random Forest, Logistic Regression, SVM Classifier. In terms ...
Added: November 7, 2019