Enhancing newspaper article keyword generation tools in institutional repositories using AI: efficiency and accuracy

The significant advancements of Artificial Intelligence (AI) have made a substantial impact on institutional repository management. This study examines the deployment of AI technologies, specifically natural language processing (NLP) and machine learning algorithms, to enhance keyword generation for newspaper articles. By automating the identification of relevant keywords, AI improves the discoverability, organization, and retrieval of resources within institutional repositories. The study presents a comparative analysis of AI-generated keywords versus manually curated ones, showcasing improvements in efficiency, accuracy, and relevance. Key findings indicate that AI-driven keyword generation facilitates better indexing and search capabilities, leading to increased visibility. The integration of AI in this context not only streamlines repository management but also significantly benefits researchers, librarians, and institutional stakeholders by ensuring a more efficient and user-friendly repository system. This study aims to highlight the transformative potential of AI in keyword generation, proposing a scalable and innovative approach to enhancing institutional repository functionalities.

Image 113821.pdf - Presentation Restricted to Repository staff only until 21 November 2024. Download (23MB)

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