A Comprehensive Review of Methods, Frameworks, and Domains for Metadata Extraction from Scientific Texts

Authors

  • Saxi Soni Department of Computer Engineering (Software Engineering), Ipcowala Institute of Engineering and Technology, Dharmaj, Gujarat Technological University, Gujarat, India Author
  • Prof. Patel Ketankumar Professor, Department of Computer Engineering (Software Engineering), Ipcowala Institute of Engineering and Technology, Dharmaj, Gujarat Technological University, Gujarat, India Author
  • Prof. Zeel Nakum Professor, Department of Computer Engineering (Software Engineering), Ipcowala Institute of Engineering and Technology, Dharmaj, Gujarat Technological University, Gujarat, India Author

DOI:

https://doi.org/10.32628/CSEIT261218

Keywords:

Metadata Extraction, Scientific Text Mining, Information Extraction, Scholarly Documents, Machine Learning

Abstract

Metadata extraction from scientific texts plays a crucial role in enabling efficient organization, retrieval, and analysis of scholarly knowledge. With the exponential growth of scientific publications across disciplines, manual metadata annotation has become infeasible, motivating the development of automated and semi-automated extraction techniques. This review paper presents a comprehensive analysis of recent advances in metadata and structured information extraction from scientific documents. It explores traditional rule-based methods, machine learning approaches, deep learning architectures, and emerging large language model-based frameworks. The paper also examines domain-specific applications, including systematic reviews, digital libraries, scientific repositories, and open journal systems. By synthesizing findings from recent literature, this study highlights key research trends, strengths, and limitations of existing methods. Furthermore, it identifies major challenges such as document heterogeneity, semantic ambiguity, evaluation complexity, and human–machine collaboration. The review aims to provide researchers with a structured understanding of current methodologies and open research directions, thereby supporting the development of robust, scalable, and high-precision metadata extraction systems for scientific knowledge management.

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Published

15-01-2026

Issue

Vol. 12 No. 1 (2026): January-February

Section

Research Articles

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Copyright (c) 2026 International Journal of Scientific Research in Computer Science, Engineering and Information Technology

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Saxi Soni, Prof. Patel Ketankumar, and Prof. Zeel Nakum, “A Comprehensive Review of Methods, Frameworks, and Domains for Metadata Extraction from Scientific Texts”, Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, vol. 12, no. 1, pp. 141–146, Jan. 2026, doi: 10.32628/CSEIT261218.