Neural network technology for detecting errors in text documents

Udovenko S. G.; Zatkhey V. A.; Teslenko O. V.

Please use this identifier to cite or link to this item: https://repository.hneu.edu.ua/handle/123456789/39115

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DC Field	Value	Language
dc.contributor.author	Udovenko S. G.	-
dc.contributor.author	Zatkhey V. A.	-
dc.contributor.author	Teslenko O. V.	-
dc.date.accessioned	2026-03-23T12:12:51Z	-
dc.date.available	2026-03-23T12:12:51Z	-
dc.date.issued	2025	-
dc.identifier.citation	Udovenko S. G. Neural network technology for detecting errors in text documents / S.G. Udovenko, V.A. Zatkhey, O.V. Teslenko // ScientificWorldJournal. – November 2025. – Svishtov,Bulgaria, 2025. - Issue №34. – Part 1. – P. 210-221.	uk_UA
dc.identifier.uri	https://repository.hneu.edu.ua/handle/123456789/39115	-
dc.description.abstract	The goal of this work is to develop a modified technology for error detection in text documents using a multilayer perceptron neural network. The proposed technology is implemented using an autoassociative neural network trained on a corpus of parallel texts containing distorted and corrected sentences. The feasibility of using the principal component method for preprocessing input text data is investigated. The test results confirm the effectiveness of the application of the studied technology for detecting errors in polythematic text documents.	uk_UA
dc.language.iso	en	uk_UA
dc.subject	electronic text analysis	uk_UA
dc.subject	error detection in text documents	uk_UA
dc.subject	neural network modeling	uk_UA
dc.subject	principal component method	uk_UA
dc.subject	autoassociative three-layer perceptron	uk_UA
dc.title	Neural network technology for detecting errors in text documents	uk_UA
dc.type	Article	uk_UA
Appears in Collections:	Статті (ІСУ)

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