KFU. Card publication. A System for Processing Large Volumes of Text Information Using Neural Networks

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

A SYSTEM FOR PROCESSING LARGE VOLUMES OF TEXT INFORMATION USING NEURAL NETWORKS

Form of presentation

Articles in international journals and collections

Year of publication

2024

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Authors, employees of KFU

Akhmedova Alfira Mazitovna, author

Bibliographic description in the original language

Akhmedova A, Zhazhneva I, Matrenina O., A System for Processing Large Volumes of Text Information Using Neural Networks//Proceedings - 2024 International Russian Smart Industry Conference, SmartIndustryCon 2024. - 2024. - Vol., Is.. - P.471-476.

Annotation

This paper presents the implementation of a system for summarizing large amounts of text information using neural networks. Relevance of this system is due to the need to obtain a large amount of knowledge in a very short time. The system works through the telegram bot interface. Telegram bot provides the ability to generate an annotation for input text and output the result as text file. Programming language used is Python. PostgreSQL database management system was chosen to store the data. To implement the system, data was collected, with the help of which the model was further trained. A parser was implemented to collect data. Multilingual mBART model was chosen as the initial model. To evaluate the model of summarization problem, the ROUGE metric was used. The result is a system that allows to obtain reliable information in compressed, accessible form, namely in the form of a text file, for further analysis.

Keywords

text summarization, neural networks, artificial intelligence, telegram bot, transfer learning, text processing

The name of the journal

Proceedings - 2024 International Russian Smart Industry Conference, SmartIndustryCon 2024

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193269501&doi=10.1109%2fSmartIndustryCon61328.2024.10515540&partnerID=40&md5=d71cda589f44c5d3096c70cc02b74de3

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

https://repository.kpfu.ru/eng/?p_id=301390&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, Matrenina O., A System for Processing Large Volumes of Text Information Using Neural Networks//Proceedings - 2024 International Russian Smart Industry Conference, SmartIndustryCon 2024. - 2024. - Vol., Is.. - P.471-476.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=301390&p_lang=2	ru_RU
dc.description.abstract	Proceedings - 2024 International Russian Smart Industry Conference, SmartIndustryCon 2024	ru_RU
dc.description.abstract	This paper presents the implementation of a system for summarizing large amounts of text information using neural networks. Relevance of this system is due to the need to obtain a large amount of knowledge in a very short time. The system works through the telegram bot interface. Telegram bot provides the ability to generate an annotation for input text and output the result as text file. Programming language used is Python. PostgreSQL database management system was chosen to store the data. To implement the system, data was collected, with the help of which the model was further trained. A parser was implemented to collect data. Multilingual mBART model was chosen as the initial model. To evaluate the model of summarization problem, the ROUGE metric was used. The result is a system that allows to obtain reliable information in compressed, accessible form, namely in the form of a text file, for further analysis.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	text summarization	ru_RU
dc.subject	neural networks	ru_RU
dc.subject	artificial intelligence	ru_RU
dc.subject	telegram bot	ru_RU
dc.subject	transfer learning	ru_RU
dc.subject	text processing	ru_RU
dc.title	A System for Processing Large Volumes of Text Information Using Neural Networks	ru_RU
dc.type	Articles in international journals and collections	ru_RU