title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ñ ÑÐµÑ Ð½Ð¾Ð»Ð¾Ð³Ð¸ÐµÐ¹ Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð³ÐµÐ½ÐµÑÐ°ÑÐ¸Ð¸ ÑÐµÐºÑÑÐ¾Ð² Ð½Ð° ÐµÑÑÐµÑÑÐ²ÐµÐ½Ð½ÑÑ ÑÐ·ÑÐºÐ°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: Artificial Neural Networks with Deep Learning Technology Application for Natural Languages Texts Generation
Creators: name: Ð¨Ð°ÑÐ¸Ð½, ÐÐµÐ¹Ð½
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: 2019
Subjects: ÐÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
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Ð³ÐµÐ½ÐµÑÐ°ÑÐ¸Ð²Ð½ÑÐµ ÑÐ¾ÑÑÑÐ·Ð°ÑÐµÐ»ÑÐ½ÑÐµ Ð¼ÐµÑÐ¾Ð´Ñ

description: Ð­ÑÐ° ÑÐ°Ð±Ð¾ÑÐ° Ð¾ÑÐ½Ð¾ÑÐ¸ÑÑÑ Ðº ÑÑÐµÑÐµ Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð´Ð»Ñ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸ ÐµÑÑÐµÑÑÐ²ÐµÐ½Ð½Ð¾Ð³Ð¾ ÑÐ·ÑÐºÐ°, Ð¼Ñ Ð¿ÑÐ¾Ð²ÐµÐ»Ð¸ ÑÐ¼Ð¿Ð¸ÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð³ÐµÐ½ÐµÑÐ°ÑÐ¸Ð¸ ÑÐµÐºÑÑÐ° Ð¸ Ð¿ÑÐ¾Ð²ÐµÐ»Ð¸ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ð¼ÐµÐ¶Ð´Ñ Ð²Ð°ÑÐ¸Ð°ÑÐ¸Ð¾Ð½Ð½ÑÐ¼ Ð¼ÐµÑÐ¾Ð´Ð¾Ð¼ Ð°Ð²ÑÐ¾ÑÐ½ÐºÐ¾Ð´ÐµÑÐ° Ð¸ Ð¿Ð¾ÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½ÑÐ¼ Ð³ÐµÐ½ÐµÑÐ°ÑÐ¸Ð²Ð½ÑÐ¼ ÑÐ¾ÑÑÑÐ·Ð°ÑÐµÐ»ÑÐ½ÑÐ¼ Ð¼ÐµÑÐ¾Ð´Ð¾Ð¼. Ð Ð¿ÐµÑÐ²Ð¾Ð¹ Ð³Ð»Ð°Ð²Ðµ Ð±ÑÐ»Ð¸ Ð¾Ð¿Ð¸ÑÐ°Ð½Ñ Ð¾ÑÐ½Ð¾Ð²Ð½ÑÐµ Ð¿ÐµÑÐµÐ´Ð¾Ð²ÑÐµ Ð¼ÐµÑÐ¾Ð´Ñ Ð³ÐµÐ½ÐµÑÐ°ÑÐ¸Ð¸ ÑÐµÐºÑÑÐ° Ñ Ð¿Ð¾Ð´ÑÐ¾Ð±Ð½ÑÐ¼ Ð¾Ð±ÑÑÑÐ½ÐµÐ½Ð¸ÐµÐ¼ Ð²Ð°ÑÐ¸Ð°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð°Ð²ÑÐ¾ÑÐ½ÐºÐ¾Ð´ÐµÑÐ° Ð¸ Ð¿Ð¾ÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ Ð³ÐµÐ½ÐµÑÐ°ÑÐ¸Ð²Ð½Ð¾Ð¹ ÑÐ¾ÑÑÑÐ·Ð°ÑÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐµÑÐ¸. ÐÐ¾ Ð²ÑÐ¾ÑÐ¾Ð¹ Ð³Ð»Ð°Ð²Ðµ Ð¼Ñ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð»Ð¸ Ð´ÐµÑÐ°Ð»Ð¸ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð¸ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÑ, ÐºÐ¾ÑÐ¾ÑÑÐµ Ð¼Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸, Ð¼Ñ ÑÐ°ÐºÐ¶Ðµ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð»Ð¸, ÐºÐ°Ðº Ð¼Ñ Ð¿Ð¾Ð´Ð³Ð¾ÑÐ¾Ð²Ð¸Ð»Ð¸ Ð½Ð°Ñ Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ Ð´Ð»Ñ ÑÑÐ¾Ð¹ Ð·Ð°Ð´Ð°ÑÐ¸. Ð ÑÑÐµÑÑÐµÐ¹ Ð³Ð»Ð°Ð²Ðµ Ð¼Ñ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð¸Ð»Ð¸ Ð½Ð°ÑÐ¸ ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÑ Ð¸ ÑÐ¾, ÐºÐ°Ðº Ð¸Ð´ÐµÑ Ð¿ÑÐ¾ÑÐµÑÑ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. Ð Ð¿Ð¾ÑÐ»ÐµÐ´Ð½ÐµÐ¹ Ð³Ð»Ð°Ð²Ðµ Ð¼Ñ ÑÐ¾Ð¾Ð±ÑÐ¸Ð»Ð¸ Ð¾ Ð½Ð°ÑÐ¸Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ°Ñ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ð¹ Ð¸ Ð¼ÐµÑÑÐ¸Ðº, ÐºÐ¾ÑÐ¾ÑÑÐµ Ð¿Ð¾ÐºÐ°Ð·ÑÐ²Ð°ÑÑ, Ð½Ð°ÑÐºÐ¾Ð»ÑÐºÐ¾ ÑÐ¾ÑÐ¾ÑÐ¾ ÑÐ³ÐµÐ½ÐµÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÐµ Ð¾Ð±ÑÐ°Ð·ÑÑ.
description: This work belongs to the sphere of deep learning and artificial neural network for natural language processing, we made an empirical research on deep learning methods for text generation, and we performed comparisons between variational autoencoder method and sequence generative adversarial method. In chapter 1 main advanced methods of text generation, were described with detailed explanation variational autoencoder and sequence generative adversarial network. In chapter 2 we showed implementation details and architectures we used, we showed as well how we prepared our dataset for this task. In chapter 3 we presented our experiments and how the training process goes on. In the last chapter we reported our results with comparisons and metrics that shows how well are the generated samples.