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HENGKI TAMANDO
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INDONESIA
Journal Basic Science and Technology
Published by Institute of Computer Science
ISSN : 20898185     EISSN : 28081498     DOI : https://doi.org/10.35335/jbst
Core Subject : Science, Engineering,
Biochemistry, Genetics & Molecular Biology Computer Science & IT Electrical & Electronics Engineering Materials Science & Nanotechnology Mechanical Engineering
This journal is devoted to identifying, mapping, understanding, and interpreting new trends and patterns in the development of science & technology especially in developing countries in this world. The journal endeavors to highlight science & technology development from different perspectives. The aim is to promote broader dissemination of the results of scholarly endeavors into a broader subject of knowledge and practices and to establish an effective means of communication among academic and research institutions, policymakers, government agencies, and persons concerned with the complex issue of science & technology development
Arjuna Subject : Umum - Umum
Articles 1 Documents
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Search results for , issue "Vol 14 No 1 (2025): February: Basic Science and Technology" : 1 Documents clear
Enhancing Digital Library Search Efficiency Through Artificial Intelligence: An Analysis of Fast Search Technologies Siringo, Rimmar; Abighael, Aaron; Gabriela, Jill Hannah
Journal Basic Science and Technology Vol 14 No 1 (2025): February: Basic Science and Technology
Publisher : Institute of Computer Science (IOCS)

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Abstract

The advent of Artificial Intelligence (AI) has transformed digital library search systems, offering unprecedented speed, accuracy, and personalization. This research explores the implementation and benefits of AI-powered fast search technologies in digital libraries, comparing them with traditional methods such as keyword-based and Boolean searches. The study examines the efficiency, scalability, and user experience improvements made possible by advanced AI techniques, including natural language processing and semantic search. The findings reveal that AI-driven systems significantly enhance the retrieval process, enabling more relevant and context-aware search results, even for complex queries. Additionally, the study highlights the personalization of search experiences, making digital libraries more accessible and user-friendly for diverse audiences. However, challenges such as data quality, technical complexity, ethical considerations, and high implementation costs are identified as barriers to adoption. This research concludes that while AI technologies hold immense promise in revolutionizing digital libraries, addressing these challenges through collaborative efforts and robust frameworks is crucial. By doing so, digital libraries can fully leverage AI's potential to advance knowledge dissemination and support academic and research communities.

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