Algorithmics for aggregating unique digital identifiers of potential applicants localized within a regional agglomeration

the article proposes an algorithmic approach to aggregating unique digital identifiers of potential university applicants in order to create a unified information space for analytical support in managing educational policy and workforce planning in the region. The necessity of developing a new algorithm that ensures high accuracy and completeness of data aggregation is substantiated to improve the effectiveness of strategic planning mechanisms in education and align workforce training with the needs of the regional labor market. The algorithm involves the use of the VKontakte social network to build a database of students from educational institutions such as schools, lyceums, and gymnasiums. Users of this social network from the Astrakhan region aged 15–17 years, who are potentially interested in higher education, were selected as the research sample. The “Materials and Methods” section contains a visual diagram illustrating the data processing logic. The paper describes the structure of the algorithm, including stages of preprocessing, matching, and data aggregation. The study is applied in nature and can be used to create a database of potential applicants, contributing to the optimization of university admission processes, the development of personalized educational pathways, the economically justified allocation of state-funded places, and the improvement of the efficiency of regional educational infrastructure financing.

unique digital identifiers, data aggregation, potential applicants, information space, VKontakte, regional agglomeration, educational policy, labor market, digital economy, mathematical methods in economics