K.A. Kuznetsova1

1 The National University of Science and Technology MISIS
1 k.a.kuznecova@gmail.com

Problem statement. About 70% of companies in Russia are experiencing staff shortages, which reached about 4.8 million people by the end of 2023. In this regard, it is necessary to develop an information system aimed at solving the problem of managing integration processes in the field of educational policy of universities and personnel policy of enterprises. Goal. The purpose of this study is to develop a recommendation information system for collecting, storing, systematizing and comparing information on the areas of graduate training and current vacancies to improve the effectiveness of interaction between educational organizations and enterprises. Results. A graph-theoretic approach was used as a model of knowledge representation, in which a cognitive graph was built based on information from open sources. To build graph representations, 581 records of specialties and universities were collected, including 58156 course names, as well as 29684 open vacancies in 266 cities of Russia. Practical significance. The developed tools make it possible to provide a deep understanding of the links between the areas of graduate training and vacancies through visualization tools. To establish relationships, a mathematical apparatus was developed that combines transposition operations with neuromorphic modeling algorithms. The proposed approach allows you to create personalized recommendations and is useful both for students choosing specialties and universities, and for companies looking for specialized specialists.

Кузнецова К.А. Постановка задачи управления интеграционными процессами в сфере образовательной и кадровой политики методом когнитивных графов // Наукоемкие технологии. 2024. Т. 25. № 4. С. 60−66. DOI: https://doi.org/10.18127/ j19998465-202404-06

1. Katchenko M.M. Problemy dejstvuyushchej kadrovoj politiki organizacii. Postulat. 2024. № 1, yanvar' (in Russian).
2. Mel'nikova M.V., Hlopenko O.V. Aktual'nye problemy formirovaniya effektivnoj kadrovoj politiki organizacii. Ekonomika i biznes: teoriya i praktika. 2023. № 9 (103). S. 149–151 (in Russian).
3. Subbotina T.N., Mirenkova V.O. Problema kadrovoj obespechennosti rossijskih organizacij: analiz pokazatelej rynka truda 2022–2023 gg. //Dnevnik nauki. 2023. № 8. S. 80 (in Russian).
4. Tomakova I.A., Fedorova A.R., Bredihin V.V. Regional'nyj rynok truda v sfere turizma i gostinichnoj industrii v usloviyah transformacii rossijskoj ekonomiki. Izv. Yugo-Zapadnogo gosudarstvennogo universiteta. Ser.: Ekonomika. Sociologiya. Menedzhment. 2024. T. 13. № 6. S. 84–97 (in Russian).
5. Girya I.A. Ponyatijnyj graf kak osnova vedeniya modeli znanij. Mashinostroenie i komp'yuternye tekhnologii. 2011. № 5. S. 11 (in Russian).
6. Hlyzov E. Upravlenie dannymi na osnove grafov znanij. Otkrytye sistemy. SUBD. 2018. № 3. S. 28–28 (in Russian).
7. Bazenkov N. i dr. Obzor informacionnyh sistem analiza social'nyh setej. Upravlenie bol'shimi sistemami: sbornik trudov. 2013. № 41. S. 357–394 (in Russian).
8. Manzhosov A.V., Bolodurina I.P. Metod avtomatizirovannogo postroeniya grafa znanij svyaznosti formal'nyh modelej norm i trebovanij v oblasti informacionnoj bezopasnosti. Vestnik UrFO. Bezopasnost' v informacionnoj sfere. 2022. № 2 (44). S. 49–56 (in Russian).
9. Gurin V.S. i dr. Predstavlenie znanij v vide grafa: osnovnye tekhnologii i podhody. Sovremennye informacionnye tekhnologii i IT-obrazovanie. 2019. T. 15. № 4. S. 932–944 (in Russian).
10. Mazutskij N.M. Imitacionnoe modelirovanie kognitivnymi grafami na primere inflyacionnyh vozmushchenij. Izv. vuzov. Ser.: Ekonomika, finansy i upravlenie proizvodstvom. 2021. № 4 (50). S. 156–164 (in Russian).
11. Maksimov V.I., Kornoushenko E.K., Kachaev S.V. Kognitivnye tekhnologii dlya podderzhki prinyatiya upravlencheskih reshenij. Informacionnoe obshchestvo. 1999. T. 2. S. 50–54 (in Russian).
12. Palvanov M.R. i dr. Ispol'zovanie dannyh o navykah studentov dlya sozdaniya personalizirovannyh rezyume s pomoshch'yu nejronnyh setej. Otvetstvennyj redaktor. 2023. S. 10 (in Russian).
13. Korovin D.I., Mazutskij N.M. Primenenie teorii sbalansirovannyh kognitivnyh grafov dlya resheniya zadach upravleniya ekonomicheskimi processami. Sovremennaya matematika i koncepcii innovacionnogo matematicheskogo obrazovaniya. 2021. T. 8. № 1. S. 152–168 (in Russian).
14. Gorelova G.V. i dr. Kognitivnyj podhod k issledovaniyu uslovij razvitiya regional'noj sistemy. Izv. Yuzhnogo federal'nogo universiteta. Ser.: Tekhnicheskie nauki. 2004. T. 44. № 9. S. 110–122 (in Russian).
15. Korovin D.I. O primenenii kognitivnyh grafov dlya analiza kachestvennyh harakteristik social'no-ekonomicheskih processov: korrupciya v vuze. Izvestiya vysshih uchebnyh zavedenij. Ser.: Ekonomika, finansy i upravlenie proizvodstvom. 2020. № 2 (44). S. 67–72 (in Russian).
16. Gorelova G.V., Zaharova E.N., Ginis L.A. Kognitivnyj analiz i modelirovanie ustojchivogo razvitiya social'no-ekonomicheskih sistem. 2005 (in Russian).
17. Kuznecov O.P., Zhilyakova L.Yu. Slozhnye seti i kognitivnye nauki. Nejroinformatika. 2015. T. 1. S. 18 (in Russian).
18. «Vuzopediya» – sajt dlya abiturientov i interesuyushchihsya vysshim obrazovaniem. URL: https://vuzopedia.ru/ (data obrashcheniya: 21.04.2024) (in Russian).
19. Rabota v Moskve, poisk personala i publikaciya vakansij. URL: https://hh.ru/ (data obrashcheniya: 21.04.2024) (in Russian).
20. Kuznecova K.A. Funkcii i arhitektura ekspertno-analiticheskoj sistemy v sfere obrazovatel'nyh i kadrovyh processov. Nelinejnyj mir. 2024. T. 22. № 2. S. 54–63. DOI: https://doi.org/10.18127/j20700970-202402-06