Abstract

Nowadays, important mechanisms of study are content and techniques of its creation, the problem of influencing the target audience, which itself seeks to shape communication processes. Internet content occupies a position of powerful communication technology, which continues to grow rapidly and gain influence. Creating a large number of advertisements, especially texts, is extremely expensive. Therefore, it is worth considering how generate these texts automatically. In this regard, it is possible to assume that the development of a method of forming the context of advertising and target audience based on learning associative rules is relevant and can increase the effectiveness of advertising, and thus reduce the cost of online advertising of higher education institutions. The input data used a survey of students majoring in Computer Science, regarding admission. The 152 students took part in the survey and answered 10 questions. The experimental results confirmed, the proposed method enabled to increase the effectiveness of advertising on social networks at least in 23%, and reduce the price in 90%.

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