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Integration Online Service for the Selection of Specialists by a Campaign Using Machine Learning Algorithms

ФИО студента: Nikita Karuk

Руководитель: Nadejda Konstantinovna Trubochkina

Кампус/факультет: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Программа: Information Science and Computation Technology (Bachelor)

Оценка: 7

Год защиты: 2021

In the modern IT world, the search for in-demand employees is a key process for enterprises. There are many online services that make it easy to find the right specialists, but machine learning algorithms are not implemented everywhere. As a result, this problem becomes urgent, since this technology selects candidates for suitable vacancies as accurately as possible. This approach is a novelty in the modern IT world, because thanks to its implementation, enterprises will be able to better select the specialists in demand. Also, choosing the merits of other services, it is necessary to provide an online service with an intuitive and understandable user interface, which will integrate with Google mail for sending notifications. The goal of the graduation work is to create of an online integration service that, using artificial intelligence, will determine the suitability of specialists for a given company. As a result, the following tasks were solved: • The structure of the online service has been developed; • A Database has been developed, which stores data on all specialists and administrators; • The back-end part developed: design patterns, using various frameworks (SpringFramework, Hibernate, Vue.js); • A convenient and intuitive interface has been developed, as well as an optimal system for responding to requests; • Developed Google-authorization for users; • Integration of notifications with Google mail has been developed; • A machine learning algorithm has been developed to find the specialists in demand; • Experiments and testing of the online integration service have been carried out. The volume of the graduation work is 46 pages. The number of illustrations - 41. The number of references - 10. The number of tables – 1.

Full text (added May 13, 2021)

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