Enhancing Digital Library Search Efficiency Through Artificial Intelligence: An Analysis of Fast Search Technologies

Rimmar Siringo; Aaron  Abighael; Jill Hannah  Gabriela

Authors

Rimmar Siringo Program Studi Sistem Informasi, Institut Teknologi dan Bisnis Indonesia
Aaron Abighael Prodi Teknik Informatika, Fakultas Informatika dan Komputer, Universitas Kristen Indonesia Paulus
Jill Hannah Gabriela Prodi Teknik Informatika, Fakultas Informatika dan Komputer, Universitas Kristen Indonesia Paulus

Keywords:

Artificial Intelligence (AI), Digital Libraries, Fast Search Technology, Information Retrieval, Semantic Search

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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