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  • Создание специальных корпусов текстов на основе расширенной платформыTXM
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News
May 12, 2026
‘Any Real-Economy Company Can Use Our Products
The HSE Centre for Financial Research and Data Analytics combines fundamental and applied work, including in areas unique to Russia such as the connection between sentiment in the media and social networks and financial markets. The HSE News Service spoke with the centre’s director, Professor Tamara Teplova, about its work.
May 7, 2026
Researchers Find More Effective Approach to Revealing Majorana Zero Modes in Superconductors
An international team of researchers, including physicists from HSE MIEM, has demonstrated that nonmagnetic impurities can help more accurately reveal Majorana zero modes—quantum states considered promising building blocks for quantum computing. The researchers found that these impurities shift the energy levels that typically obscure the Majorana signal, while leaving the mode itself largely unaffected, thereby making its spectral peak more distinct. The study has been published in Research.
May 6, 2026
The Future of Cardiogenetics Lies in Artificial Intelligence
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a program capable of analysing regions of the human genome that were previously inaccessible for accurate interpretation in genetic testing. The program adapts large generative AI (GenAI) models for cardiogenetics to predict how specific mutations affect the function of individual genes.

 

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Создание специальных корпусов текстов на основе расширенной платформыTXM

Системы высокой доступности. 2018. Т. 14. № 3. С. 76–81.
Лаврентьев А. М., Смирнов И. В., Соловьев Ф. Н., Суворова М. И., Fokina A., Chepovskiy A.

The extension of the TXM platform for case analysis is considered. It is proposed to use the allocation of pseudo-words in words of text on the basis of the method of structural schemes and the identification of nominal groups in the structure of the text forselecting subcorps in terms of parameters. The results of the analysis of the corpus of extremist texts are described.

Priority areas: IT and mathematics
Language: Russian
Full text
DOI
Keywords: корпусная лингвистикаанализ соответствийcorpora linguisticsspecificityautomatic morphological analysisавтоматический морфологический анализTXM platformdetecting extremist textsплатформаTXMспецифичностьanalysis of correspondenceэкстремистские тексты.
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