Neural network technology for detecting errors in text documents

dc.contributor.author	Udovenko S. G.
dc.contributor.author	Zatkhey V. A.
dc.contributor.author	Teslenko O. V.
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.
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.
dc.identifier.uri	https://repository.hneu.edu.ua/handle/123456789/39115
dc.language.iso	en
dc.subject	electronic text analysis
dc.subject	error detection in text documents
dc.subject	neural network modeling
dc.subject	principal component method
dc.subject	autoassociative three-layer perceptron
dc.title	Neural network technology for detecting errors in text documents
dc.type	Article

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