title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð¸ Ð³ÐµÐ½ÐµÑÐ¸ÑÐµÑÐºÐ¸Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð´Ð»Ñ Ð¼Ð¾Ð´ÐµÑÐ°ÑÐ¸Ð¸ ÐºÐ¾Ð½ÑÐµÐ½ÑÐ°
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: Application of artificial neural networks and genetic algorithms for content moderation
Creators: name: Ð¨ÑÑÐºÐ°Ð½Ð¾Ð²Ð°, ÐÐºÐ°ÑÐµÑÐ¸Ð½Ð°
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: 2021
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÐÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
Ð¼Ð¾Ð´ÐµÑÐ°ÑÐ¸Ñ ÐºÐ¾Ð½ÑÐµÐ½ÑÐ°
Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð³ÐµÐ½ÐµÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼

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description: The theme of the final qualifying work: "The use of artificial neural networks and genetic algorithms for content moderation." This paper explores the issue of the relevance of user content and its moderation for business. The history of the development of moderation processes and moderation rules is described. The methods of user content moderation and their features are considered. Comparison of manual and automatic methods of moderation is carried out. Automatic moderation is described in detail, how it works, its advantages and disadvantages. The most popular solutions for automatic moderation are presented. The types of artificial neural networks (ANNs) and methods of their training with and without a genetic algorithm have also been investigated. A convolutional model of an artificial neural network is described and investigated in the most detail. The genetic algorithm and the stages of its work have been studied and described. Then, a convolutional ANN was designed and implemented in Python using the Tensorflow library. The model is trained in two ways: using standard training and using a genetic algorithm. An experimental study of the effectiveness of the implemented ANN and the genetic algorithm for solving the problem of content moderation has been carried out. The conclusion is made about the applicability of genetic algorithms for content moderation tasks.