title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¸ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ ÑÐ¸ÑÑÐµÐ¼Ñ Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð°Ð½Ð½Ð¾ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÐµÐºÑÑÐ° Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐµÐ¾ÑÐ¸Ð¸ ÑÐ¸ÑÐ¾ÑÐ¸ÑÐµÑÐºÐ¾Ð¹ ÑÑÑÑÐºÑÑÑ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 analysis of the automatic text summarization system based on rhetorical structure theory
Creators: name: Ð¨ÐºÑÑÐ¸Ð½Ð°, ÐÐ°Ñ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: 2020
Subjects: Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð°Ð½Ð½Ð¾ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐµÐºÑÑÐ°
ÑÐµÐ¾ÑÐ¸Ñ ÑÐ¸ÑÐ¾ÑÐ¸ÑÐµÑÐºÐ¾Ð¹ ÑÑÑÑÐºÑÑÑÑ
Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ° ÐµÑÑÐµÑÑÐ²ÐµÐ½Ð½Ð¾Ð³Ð¾ ÑÐ·ÑÐºÐ°
Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
automatic text summarization
rhetorical structure theory
natural language processing
neural networks

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description: This work belongs to the field of automatic natural language processing. It gives an overview of the current state of the text summarization problem, limitations of the existing methods are analyzed. The possibility of applying Rhetorical Structure Theory to this task for getting more coherent and concise summaries is considered. Existing methods for automatic rhetorical structure parsing are analyzed, as well as their advantages and disadvantages. Based on the conducted research and taking into consideration all the strengths and weaknesses of the existing methods and systems, a system consisting of three modules is proposed. The first module segments the input text, the second module identifies rhetorical relations and the third one generates a summary with respect to the rhetorical structure of the input text. The system that was developed and implemented can be used by corporate document management systems, search engines and automated library information systems, broadcasting channels and news websites. The results of the conducted experiments with the final system show that discourse analysis can be used for getting summaries of better quality and that research in this direction can be continued.