Algorithmically selects scientific events for university staff, indicating an advancement in personalized recommendations.
The paper is devoted to the development of models and algorithms that will form the basis of an intellectual agent designed to select scientific events for a university employee. Given the ever-increasing flow of official information, the relevance and practical significance of such a development is beyond doubt. The object of research in the work is the process of scientific activity of teachers, reflected in the accounting documents of the scientific activity of the staff of the department. The subject of the research is models and algorithms for the analysis of scientific activity for the formation of an appropriate teacher profile. The goal is to develop an intelligent agent based on the developed algorithmic model, which ensures the relevant selection of scientific activities for this employee based on his profile. The paper proposes a formalization of the task, develops algorithms for forming a profile of scientific activity and extracting thematic features from information letters, as well as the structure of a decision support system. The developed approach was tested on real information letters, showing its applicability to solving the problem of personalized recommendation of scientific events.
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Oleynikova et al. (2026) studied this question.
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