title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¸ Ð²Ð½ÐµÐ´ÑÐµÐ½Ð¸Ðµ ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð¿ÑÐ¾Ð´Ð°Ð¶Ð°Ð¼Ð¸ Ð¼ÐµÐ´Ð¸Ð°Ñ Ð¾Ð»Ð´Ð¸Ð½Ð³Ð° Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Development and implementation of a media holding sales management system using machine learning
Creators: name: ÐÐ¾ÑÑÑÐºÐ¾, ÐÐµÑÐ¾Ð½Ð¸ÐºÐ°
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð°ÑÐ¸Ñ
Ð¿ÑÐ¾ÑÐµÑÑÑ Ð¿ÑÐ¾Ð´Ð°Ð¶
Ð¼ÐµÐ´Ð¸Ð°ÑÑÐ½Ð¾Ðº
ÐºÐ»Ð°ÑÑÐµÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð·
Ð´Ð¸ÑÐ¿ÐµÑÑÐ¸Ð¾Ð½Ð½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð·
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
automation
sales process
media market
cluster analysis
variance analysis
machine learning

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description: The purpose of the research is the development of architecture, as well as the development of technology recommendations for the implementation of a media holding sales management system using machine learning. The research was carried out on the basis of simulated sales processes of advertising materials, as well as on the basis of data on rents of TV shows. The subject of the thesis is a sales management system in a media holding using machine learning methods. Research methods: analysis and synthesis, formalization, modeling. The main results of the study: â the simulated sales processes of advertising materials in the media holding are investigated; â the architecture of automation of sales processes of advertising materials has been developed; â cluster and variance analysis of TV ratings data was carried out; â a machine learning model for predicting TV ratings has been developed, and options for its development have been proposed. The field of application of results is a digital transformation of media holdings by automating sales processes using machine learning. The scientific novelty is the proposed architecture for automating the sales of advertising materials, which includes machine learning. As a result, a solution was developed with a module for automatic advertising placement in the broadcast network using a machine learning model. Conclusions. An architecture for automating the sales of advertising materials has been developed, and developed recommendations on technologies for implementing a media holding sales management system using machine learning have been proposed.