人工智能与机器学习在图书馆中的应用：系统综述
Application of Artificial Intelligence and Machine Learning in Libraries: A Systematic Review
AI总结：
通过系统综述32篇文献，总结了人工智能与机器学习在图书馆中的应用领域、技术及现状，发现当前研究以理论为主，部分涉及实践案例。
摘要：
随着人工智能和机器学习等前沿技术的概念和实施变得相关，学者、研究人员和信息专业人员涉足这一领域的研究。本系统文献综述旨在综合探讨人工智能和机器学习在图书馆中应用的实证研究。为实现研究目标，基于Kitchenham等人（2009）提出的原始指南进行了系统文献综述。数据来自Web of Science、Scopus、LISA和LISTA数据库。经过严格/既定的筛选过程，最终选定、审阅并分析了32篇文章，以总结图书馆中最常使用的AI和ML领域及技术。结果表明，当前与LIS领域相关的AI和ML研究主要集中于理论工作。然而，一些研究人员也强调了实施项目或案例研究。本研究将为研究人员、实践者和教育工作者提供图书馆中AI和ML的全景视图，以推动更多技术导向的方法，并预见未来的创新路径。
英文摘要：
As the concept and implementation of cutting-edge technologies like artificial intelligence and machine learning has become relevant, academics, researchers and information professionals involve research in this area. The objective of this systematic literature review is to provide a synthesis of empirical studies exploring application of artificial intelligence and machine learning in libraries. To achieve the objectives of the study, a systematic literature review was conducted based on the original guidelines proposed by Kitchenham et al. (2009). Data was collected from Web of Science, Scopus, LISA and LISTA databases. Following the rigorous/ established selection process, a total of thirty-two articles were finally selected, reviewed and analyzed to summarize on the application of AI and ML domain and techniques which are most often used in libraries. Findings show that the current state of the AI and ML research that is relevant with the LIS domain mainly focuses on theoretical works. However, some researchers also emphasized on implementation projects or case studies. This study will provide a panoramic view of AI and ML in libraries for researchers, practitioners and educators for furthering the more technology-oriented approaches, and anticipating future innovation pathways.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
