Shitov E. A. (Leading specialist, Big Data Storage and Analysis Center
Lomonosov Moscow State University (Moscow))
Rakov D. A. (Leading specialist, Big Data Storage and Analysis Center
Lomonosov Moscow State University (Moscow))
Tereshenko I. A. (Leading specialist, Big Data Storage and Analysis Center
Lomonosov Moscow State University (Moscow))
Kovrova E. S. (Leading specialist, Big Data Storage and Analysis Center
Lomonosov Moscow State University (Moscow))
Voronin T. V. (Leading specialist, Big Data Storage and Analysis Center
Lomonosov Moscow State University (Moscow))
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The article is devoted to the analysis of the developments of the Big Data Storage and Analysis Center on the basis of the Lomonosov Moscow State University in terms of natural language processing from the point of their practical potential for solving a wide range of problems, incl. from the point of the prospects for the digital transformation of the national economy of the Russian Federation and the role of natural language processing technologies in this process. The developments of the Big Data Storage and Analysis Center in the field of natural language processing are presented, the analysis of these developments is carried out in terms of the algorithm of their work, technologies in the basis, positive effects and advantages of the implementation, the current UGT. The problems, that can be solved by the practical application of these developments, incl. as part of the digital transformation of the economy of the Russian Federation, are highlighted.
Keywords:artificial intelligence, natural language processing, machine learning, text recognition, NLP, BERT, OCR.
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Citation link:
Shitov E. A., Rakov D. A., Tereshenko I. A., Kovrova E. S., Voronin T. V. Developments of the big data storage and analysis center on the basis of the Lomonosov Moscow state university in the field of natural language processing technologies // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2022. -№12/2. -С. 196-202 DOI 10.37882/2223-2966.2022.12-2.38 |
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