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Automated processing methods improve data utilization in material science, highlighting their analytic potential.
The present work proposes a method for the automated processing of full-text PDF articles in the field of material science that leverages visual, tabular, and textual data extraction techniques developed by the authors to obtain standardized representations of a selection of objects, thereby increasing the efficiency of technical data utilization. An integrative software tool built upon the method is discussed. The metrics of precision (63–99%) and recall (90–99%) calculated to assess tool performance prove the applicability of the solution proposed for domain-specific data aggregation, unification, search and management, and the potential for usage in science analytics systems.
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Khvostova et al. (2026) studied this question.
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