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  • Новые технологические тренды: выявление в текстах на базе использования гибридных моделей и анализа временных рядов паттернов данных
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News
August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
August 12, 2026
‘I Would Like My Research to Help Make the World a Calmer and Better Place
Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
August 11, 2026
‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Новые технологические тренды: выявление в текстах на базе использования гибридных моделей и анализа временных рядов паттернов данных

Информационно-измерительные и управляющие системы. 2013. Т. 11. № 5. С. 25–34.
Khoroshevsky V. F.

New technological trends identification is one of the most sophisticated, as well as the most important, tasks in the domain of S&T analysis. Nowadays, the leading methodologies within the domain are focused mainly on technological roadmapping, Foresight, data patterns and time series analysis, which is used to specify current and projected trends. The paper presents intelligent tools for trend identification in texts collections with hybrid approach based on the integration of classical statistical methods and the methods of information extraction. Several existing approaches are combined to be used for multilingual text collections of various genres. Ontologies driving text processing as well as documents’ characteristic vectors containing multiword terms are used. The results of statistical analysis of document collections are presented in the form of data patterns time series that are analyzed with structural methods of image analysis. OWL representation of extensional part of the trend ontological model is generated.

Research target: Philology and Linguistics Computer Science
Priority areas: business informatics
Language: Russian
Keywords: технологический трендизвлечение информации из текстовгибридный подход
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ARET 13, 1: Рассказ о том, как царь Эблы и царь Мари посетили Отца и Мать Богов
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Происхождение и функции «опционального» артикля hin в фарерском языке
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В настоящей статье авторы ставят задачу провести мониторинг мировых потоков патентования изобретений и полезных моделей в таких областях как робототехника, цифровые технологии, искусственный интеллект, новые материалы и новые способы конструирования для выявления ретроспективного и текущего состояния развития технологий. В целях данного исследования авторы использовали одну из самых полных баз данных патентной информации в мире - ...
Added: August 4, 2022
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