Алгоритми машинного навчання для підбору рекомендацій відео- та аудіо-контенту з урахуванням уподобань користувача

Abstract

This work is devoted to machine learning prediction methods for selecting video or audio-content recommendations based on user preferences. The purpose of the work is to conduct preparatory work for research on the effectiveness of machine learning algorithms for selecting music recommendations based on user preferences, who participate in the content recommendation process on almost all multimedia platforms. As a result of the work, preparatory work was carried out for further research, and documentation was developed for the future decision support system. This study will help other developers identify the strengths and weaknesses of the studied algorithms and identify the expediency of using them, partially or fully, in their own applications with a content recommendation functionality