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A keyword-based approach to analyzing scientific research trends: ReRAM present and future
Hyeon Kim1, Seong Hun Kim1, Jaeseon Kim1
1Department of Materials Science and Engineering (MSE), Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
Scientific Reports
|April 8, 2025
Summary
This study introduces a keyword-based method for analyzing research trends, successfully structuring the resistive random-access memory (ReRAM) field. It reveals key research communities and highlights growing interest in neuromorphic applications.
Area of Science:
- Materials Science
- Computer Science
- Information Science
Background:
- Research trend analysis is crucial for understanding scientific fields.
- The increasing volume of publications necessitates advanced analytical methods.
- Interpreting research fields topologically and temporally is challenging.
Purpose of the Study:
- To propose an automated keyword-based method for research trend analysis.
- To systematically analyze research fields by extracting keywords and constructing networks.
- To apply and validate the method on the resistive random-access memory (ReRAM) research field.
Main Methods:
- Article collection from the ReRAM research domain.
- Automated keyword extraction from scientific publications.
- Construction of a keyword network for research structuring.
Main Results:
- Identified three distinct keyword communities within ReRAM research.
- Revealed a strong correlation with the processing-structure-property-performance (PSPP) relationship.
- Observed an increasing trend in research related to neuromorphic applications.
Conclusions:
- The proposed method effectively structures the ReRAM research landscape.
- The approach provides detailed insights into research directions and dynamics.
- This keyword-based analysis is applicable to various scientific fields for trend prediction.
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