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October 19, 2026
'Cultural Studies Seeks to Understand What Lies Beneath the Surface of Everyday Things'
Maxim Zhiganov has been exploring different aspects of sound for many years—first in relation to his native Perm and then on a broader, global scale. In this interview for the HSE Young Scientists project, he talks about sound maps, the special issue of the journal Logos, and why it is important to make the familiar less clear and obvious.
October 14, 2026
At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
Neural networks are no longer simple travel assistants; now they decide what to include on the route and what to skip. Artificial intelligence changes how people perceive a place and shapes the image of tourist centres. At the II International Scientific and Practical Conference ’Information Technologies in the Preservation and Promotion of Cultural Heritage,’ researchers discussed who controls algorithmic solutions and in what ways, and whether authentic traditions get lost in them.
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.

 

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Proceedings of the first workshop on NLP applications to field linguistics

Gyeongju : International Conference on Computational Linguistics, 2022.
Chapters
Automatic Detection of Borrowings in Low-Resource Languages of the Caucasus: Andic branch
Zaitsev K., Minchenko A., , in: Proceedings of the first workshop on NLP applications to field linguistics.: Gyeongju: International Conference on Computational Linguistics, 2022. P. 34–41.
Linguistic borrowings occur in all languages. Andic languages of the Caucasus have borrowings from different donor-languages like Russian, Arabic, Persian. To automatically detect these borrowings, we propose a logistic regression model. The model was trained on the dataset which contains words in IPA from dictionaries of Andic languages. To improve model’s quality, we compared TfIdf ...
Added: September 29, 2024
Research target: Philology and Linguistics
Language: English
Text on another site
Keywords: field linguisticsNatural Language Processing (NLP)
Proceedings of the first workshop on NLP applications to field linguistics
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