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News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Компьютерное моделирование как инструмент анализа художественного текста

Филологический класс. 2023. Т. 28. № 2. С. 22–33.
Kolmogorova A., Залевская Е. Д.

The article investigates the issue of heuristic productivity of using the method of computer-assisted topic modeling for philological analysis of fiction text. The study analyzes the results of applying the algorithm of Latent Placement Dirichlet (LDA) for searching intertextual connections of motifs in two sub-corpora of fiction texts: 62 texts of different genres (stories, essays, novels, critical articles) belonging to S. Dovlatov, on the one hand, and 35 fiction works, which the writer listed in one of the letters to T. Urzhumova as the works that had deeply influenced him and should be read by everybody. The algorithm has revealed 20 themes (topics), into which all the texts were distributed. Each topic obtained was a chain of words with weights of significance for the realization of that topic. As a result of the comparison of the texts and the topics, three “text - topic” correspondences were discovered. The texts in each of the following three groups belong to one common topic: 1) B. Pilyniak’s novel “The Bare Year” and Dovlatov’s story “By the River”; 2) G. Wells’s novel “The Time Machine”, E. Hemingway’s story “The Old Man and the Sea” and Dovlatov’s story “Emigrants”; 3) A. Grin’s story “The Commandant of the Port” and Dovlatov’s essay “We Speak Different Languages”. Further philological analysis demonstrated the intersection of motifs in these groups of works of fiction. The pilot study under consideration has shown that methods of computer-assisted text analysis, including those based on machine learning, can become a philologist’s tool for experimental search, guiding the expert intuition along the path outlined by the algorithm via processing large corpus arrays.

Research target: Philology and Linguistics
Language: Russian
Full text
Keywords: intertextualityинтертекстуальностьtopic modelingтематическое моделированиеS. DovlatovС. Довлатов
Publication based on the results of:
Текст как Big Data: моделирование конвергентных процессов в языке и речи цифровыми методами (2023)
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