Scientific Journal of KubSAU

Polythematic online scientific journal
of Kuban State Agrarian University
ISSN 1990-4665
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Potapova Natalia Viktorovna

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Honorary rank

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Kuban State University
   

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potapova50@gmail.com


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The synthesis of the semantic nuclei of scientific specialties of the higher attestation commission of the russian federation and the automatic classifica-tion of articles according to scientific fields with the use of asc-analysis and "eidos" intellectual systems (on the example of scientific journal of kuban state agrarian university and its scientific specialties: mechanization, agronomy and veterinary medicine)

abstract 1451901033 issue 145 pp. 31 – 102 31.01.2019 ru 57
14 January 2019 at the website of the higher attestation Commission of the Russian Federation http://vak.ed.gov.ru/87 the information appeared: "About refining of scientific specialties and their respective fields of science where publications are included in the List of peer-reviewed scientific publications, where basic scientific results of dissertations on competition of a scientific degree of candidate of Sciences, on competition of a scientific degree of the doctor of Sciences must be published ". It is reported that according to the recommendation of the HAC for other publications included in the List of groups of scientific specialties, the work on refining scientific specialties and branches of science will be continued in 2019. This work is a continuation of the author's series of works on cognitive linguistics. It offers innovative intelligent technology to automate the solution of the problem formulated by the higher attestation Commission of the Russian Federation above. With the use of the automated system-cognitive analysis (ASC-analysis) and its programmatic toolkit which is intellectual system called "Eidos" directly on the basis of official texts of passports of scientific specialties of the higher attestation Commission of the Russian Federation, there were established their semantic kernels, and then, implemented the automatic classification of scientific texts (articles, monographs, textbooks, etc.) on the specialties and groups of specialties of the higher attestation Commission of the Russian Federation. Traditionally, this task is solved by dissertation councils, as well as editorial boards of scientific publications, i.e. by experts, on the basis of expert assessments, in an informal way, on the basis of experience, intuition and professional competence. However, the traditional approach has a number of serious drawbacks that impose significant limitations on the quality and volume of analysis. Therefore, the efforts of researchers and developers to overcome these limitations are relevant. Currently, there are all grounds to consider these restrictions as unacceptable, because they are not only necessary, but also quite possible to overcome. Thus, there is a problem, the solution of which is the subject of consideration in this article. A detailed numerical example of solving the problem on real data is given as well
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