Artificial Intelligence in Library and Information Science: A Systematic Review of Applications and Challenges
Keywords:
Artificial Intelligence, Library and Information Science, Systematic Review, Applications, ChallengesAbstract
This study aims to systematically review studies on the application of Artificial Intelligence (AI) technologies in the Library and Information Science (LIS) area. It focuses on AI associations with key LIS areas, challenges, and offers a critical insight into how AI is transforming the LIS areas. A systematic review of peer-reviewed papers (2000-2024) was conducted using Web of Science (WoS), Library, Information Science & Technology Abstracts (LISTA), and Library Literature & Information Science (LLIS). Following PRISMA guidelines, inclusion and exclusion criteria ensured rigor. VOSviewer was used for bibliometric mapping and keyword co-occurrence analysis, and studies were thematically categorized to link AI techniques and tools with LIS areas and challenges across the three periods. The review revealed that AI in LIS had progressed from experimental tools to essential components of modern information systems. Three periods were apparent: in 2000-2009, natural language processing (NLP) and artificial neural networks (ANNs) were primarily linked to Information Retrieval (IR); in 2010-2019, AI was most associated with digital libraries and library services; and in 2020-2024, more AI techniques and tools were associated with IR, and library services, particularly in digital and academic libraries to enhance library services and user experience. Unlike prior reviews that focused generally on libraries and specific areas such as information literacy, this study provides a broader analysis of AI techniques and tools across various LIS areas over three periods.
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