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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)

Вып. 19(26). M. : -, 2020.
Under the general editorship: Селегей В.

 Papers from the Annual International Conference “Dialogue” (2020). Issue 19

Chapters
RuREBus-2020 Shared Task: Russian Relaton Extraction for Business
Artemova E., Batura T., Sarkisyan V. et al., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. P. 416–432.
В статье представлены результаты соревнования по распознаванию именованных сущностей и извлечению отношений. Целью соревнования является сравнение методов извлечения сущностей и отношений на русском языке в постановке, приближенной к индустриальным задачам. В качестве исходной коллекции текстов использовался корпус Минэкономразвития РФ, содержащий программы стратегического развития. Корпус был размечен в соответствии с инструкцией, разработанной авторами статьи. В процессе ...
Added: June 11, 2020
Referential phenomena in speaker's kinetic channels
Budennaya E., Evdokimova A., Nikolaeva J. et al., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. P. 118–131.
The article addresses the relation of referential expressions and co-occurring kinetic phenomena (hand and head gestures) on the material of the RUPEX multimodal corpus. The results reflect significant differences in how individual movements and gestures are aligned with two major types of reference (full NPs vs. reduced expressions). It was initially assumed that full NPs ...
Added: June 26, 2020
Русский Конструктикон: новый лингвистический ресурс, его устройство и специфика
Эндресен А. А., Жукова В. А., Мордашова Д. Д. et al., В кн.: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. С. 241–255.
We present a new open-access electronic resource named the Russian Constructicon that offers a searchable database of Russian constructions accompanied by descriptions of their properties and illustrated with corpus examples. The project was carried out over the period 2016–2020 and at present contains an inventory of over 2200 multi-word constructions of Contemporary Standard Russian. We ...
Added: July 3, 2020
Русский Конструктикон: новый лингвистический ресурс, его устройство и специфика
Эндресен А. А., Жукова В. А., Мордашова Д. Д. et al., В кн.: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. С. 241–255.
We present a new open-access electronic resource named the Russian Constructicon that offers a searchable database of Russian constructions accompanied by descriptions of their properties and illustrated with corpus examples. The project was carried out over the period 2016–2020 and at present contains an inventory of over 2200 multi-word constructions of Contemporary Standard Russian. We ...
Added: July 3, 2020
Exploring Semantic Concreteness and Abstractness for Metaphor Identification and Beyond
Badryzlova Y., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. P. 33–47.
The paper presents a method for computing indexes of semantic concreteness and abstractness in two languages (Russian and English). These indexes are used in metaphor identification experiments in both languages; the results are either comparable to or surpass pervious work and the baselines. We analyze the obtained indexes of concreteness and abstractness to see how ...
Added: August 24, 2020
GRAMEVAL 2020 Shared Task: Russian Full Morphology and Universal Dependencies Parsing
Lyashevskaya O., Shavrina T., Trofimov I. et al., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. P. 553–569.
The paper presents the results of GramEval 2020, a shared task on Russian morphological and syntactic processing. The objective is to process Russian texts starting from provided tokens to parts of speech (pos), grammatical features, lemmas, and labeled dependency trees. To encourage the multi-domain processing, five genres of Modern Russian are selected as test data: ...
Added: August 30, 2020
Annotating and exploring code-switching in four corpora of minority languages of Russia
Dyachkov V., Khomchenkova I., Pleshak P. et al., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. P. 228–240.
Added: October 29, 2020
Валентная структура некоторых речевых предикатных слов: новые находки
Iomdin B., Иомдин Л. Л., В кн.: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. С. 400–415.
The paper discusses valency frames of a number of Russian verbal predicates whose semantics includes speech acts and, at a cetrain step of semantic decomposition, the negation, like vozražat’ ‘object, retort’, vozmuščat’sja ‘resent, be indignant’ or izvinjat’sja ‘apologize’. It is hypothesized that the frames of such predicates include a pair of propositional valencies distinctly opposed ...
Added: November 6, 2020
Чему нас учат ошибки: трудности при обработке слов с частотными орфографическими ошибками
Чернова Д. А., Алексеева С. В., Slioussar N., В кн.: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. С. 147–159.
Орфографические ошибки — страшная напасть, но мы привыкли думать, что терпение и труд помогут с ней справиться. Однако, даже если мы сами научились писать правильно то или иное слово, никто не может уберечь нас от ошибок, сделанных другими. Эта проблема стала особенно актуальной сейчас, с появлением многочисленных электронных СМИ, чатов, социальных сетей, где колоссальные массивы текстов публикуются без ...
Added: November 20, 2020
Dialogue management using extended discourse trees
Ilvovsky D., Galitsky B., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. P. 361–371.
In this paper we learn how to manage a dialogue relying on discourse of its utterances. We consider two complementary approaches of dialogue management based on the discourse text analysis to extend the abilities of the interactive information retrieval-based chat bot. ...
Added: November 27, 2020
Modeling lemma frequency bands for lexical complexity assessment of Russian texts
Blinova O. V., Tarasov N., Blekanov I. et al., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. P. 76–92.
The paper is devoted to the problem of modeling general-language frequency using data of large Russian corpora. Our goal is to develop a methodology for forming a consolidated frequency list which in the future can be used for assessing lexical complexity of Russian texts. We compared 4 frequency lists developed from 4 corpora (Russian National Corpus, ...
Added: December 12, 2022
Research target: Computer Science Philology and Linguistics
Priority areas: humanitarian IT and mathematics
Language: Russian
Text on another site
Keywords: компьютерная лингвистикаcomputational linguisticsинтеллектуальные технологииintellectual technologies
Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)
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