The system for the automatic generation, processing, and management of document metadata in digital collections
Main Article Content
Abstract
The publishing cycle is currently undergoing significant technological changes: automated publication management systems are being implemented, neural network technologies are being used for content processing, and tools for the intelligent analysis of scientific data are being actively developed. One of the key trends is the automation of the publishing cycle, aimed at accelerating manuscript processing, improving the quality of metadata, and ensuring the interoperability of information resources. In this context, metadata serves as a connecting element for machine processing and navigation within the scientific knowledge space, ensuring the structuring, interpretation, and integration of information into digital library systems. However, metadata for scientific publications often contain errors, inaccuracies, or are incomplete, and their manual creation and refinement are time-consuming and do not ensure high accuracy. The aim of this work is to design and develop a system for the automatic generation, processing, and management of metadata for scientific documents based on data obtained from scientific publication search services and open knowledge bases. The system can be used to automate the process of extracting, refining, and supplementing the metadata of scientific publications for the purpose of subsequently creating electronic collections of scientific documents.
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References
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