Registration Number
0226U000734,
(0125U003624)
, R & D reports
Title
Development of prepress preparation methods for electronic publications using artificial intelligence
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Розроблення теоретико-методичного забезпечення та формування практичних рекомендацій щодо методів додрукарської підготовки електронних видань з використанням штучного інтелекту
Head
Serhii H. Udovenko, Доктор технічних наук
Registration Date
15-01-2026
Organization
Simon Kuznets Kharkiv National University of Economics
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Improvement of theoretical and methodological support and development of practical recommendations on prepress preparation methods for electronic publications using artificial intelligence; increasing work productivity (reducing the time required for document analysis at the prepress stage in a printing enterprise); improving the quality of prepress preparation in a printing enterprise
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The report presents the results of research related to the automation of pre-printing processes of electronic documents that should be processed in publishing houses and printing enterprises, using artificial intelligence methods and tools.
Important aspects of the analysis of these tasks and the development of practical recommendations for the use of artificial intelligence for the automation of pre-printing processes of electronic publications are considered.
The principles of using artificial intelligence in pre-printing of electronic publications are analyzed.
Methods of information support for automated pre-printing processes of electronic documents are studied and the possibilities of improving the quality of this preparation using modern neural network technologies are considered.
Practical recommendations are developed for the use of artificial intelligence for the automation of pre-printing processes of electronic publications (including: preview and proofreading of the original electronic text; pre-printing proofreading of English-language fragments of electronic text; pre-printing proofreading of bibliographic records in electronic texts).
The results of testing the constructed models for processing test documents according to the data of test datasets are presented, which confirm the feasibility of their use in systems for analyzing electronic text documents at the stage of pre-printing. The recommendations provided in the report may be useful for use in publishing houses and printing companies, since many text documents intended for further printing require specific processing (in particular, neural network proofreading).
Product Description
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Olha Vilkhivska
Olena Peredrii
Serhii H. Udovenko
Anastasiia Kylynnyk
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2026-01-15
