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.
翻译:由于人工智能和机器学习等尖端技术的概念和实施已经变得相关,学术界、研究人员和信息专业人员都参与这一领域的研究。这一系统文献审查的目的是提供一份综合经验研究,探讨在图书馆应用人工智能和机器学习的情况。为了实现研究的目标,根据Kitchenham等人(2009年)提出的原始准则进行了系统文献审查。数据来自科学网、Scopus、LISA和ListA数据库。在严格/既定的甄选程序之后,最后挑选、审查并分析了总共32篇文章,总结了在图书馆最经常使用的AI和ML域和技术的应用情况。研究结果表明,与LIS领域相关的AI和ML研究的现状主要侧重于理论工作。然而,一些研究人员还强调了实施项目或案例研究。这项研究将为研究人员、从业人员和教育工作者提供图书馆AI和ML的全景观,以推进更面向技术的方法,并预测未来的创新途径。