KFU. Card publication. System for News Summarizing Using a Neural Network Algorithm

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

SYSTEM FOR NEWS SUMMARIZING USING A NEURAL NETWORK ALGORITHM

Form of presentation

Articles in international journals and collections

Year of publication

2024

Язык

английский

Authors, employees of KFU

Akhmedova Alfira Mazitovna, author

Bibliographic description in the original language

Akhmedova A, Zhazhneva I, Galimov G., System for News Summarizing Using a Neural Network Algorithm//RusAutoCon - Proceedings of the International Russian Automation Conference. - 2024. - Vol., Is.2024. - P.307-312.

Annotation

RusAutoCon - Proceedings of the International Russian Automation Conference

Keywords

text summarization, neural networks, Transformer architecture, mBart, telegram bot, news.

The name of the journal

RusAutoCon - Proceedings of the International Russian Automation Conference

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208270528&doi=10.1109%2fRusAutoCon61949.2024.10694002&partnerID=40&md5=da3c218ddc1f5f755ef661383a0747b8

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=308521&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Akhmedova Alfira Mazitovna	ru_RU
dc.date.accessioned	2024-01-01T00:00:00Z	ru_RU
dc.date.available	2024-01-01T00:00:00Z	ru_RU
dc.date.issued	2024	ru_RU
dc.identifier.citation	Akhmedova A, Zhazhneva I, Galimov G., System for News Summarizing Using a Neural Network Algorithm//RusAutoCon - Proceedings of the International Russian Automation Conference. - 2024. - Vol., Is.2024. - P.307-312.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=308521&p_lang=2	ru_RU
dc.description.abstract	RusAutoCon - Proceedings of the International Russian Automation Conference	ru_RU
dc.description.abstract	This paper presents implementation of a system for summarizing news using a neural network algorithm. Relevance of the development of this system is due to the need for users to receive news in a concise form, while maintaining objectivity and accuracy of information transfer. Multilingual mBART Large CC25 model was chosen as the initial model. The main source of data for further training of the model was the gazeta dataset, taken from the Hugging Face project, supplemented by a collected data set from various news sources. To determine the qualities of the trained model, ROUGE and BLEU metrics were used. When developing the summarization algorithm, Python programming language with deep learning libraries PyTorch and Fairseq were used. The system works through the telegram bot interface. Telegram bot provides the ability to generate an annotation for the required news and produce the result in form of a message. The result of this work is a system that allows to receive a news summary in form of a short message.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	text summarization	ru_RU
dc.subject	neural networks	ru_RU
dc.subject	Transformer architecture	ru_RU
dc.subject	mBart	ru_RU
dc.subject	telegram bot	ru_RU
dc.subject	news.	ru_RU
dc.title	System for News Summarizing Using a Neural Network Algorithm	ru_RU
dc.type	Articles in international journals and collections	ru_RU