Kim Cheongil, Yeom Jaesun, Jeong Seunghoo, Chung Ji-Bum
School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
School of Business Administration, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
Heliyon. 2023 Jul 27;9(8):e18766. doi: 10.1016/j.heliyon.2023.e18766. eCollection 2023 Aug.
This study analyzed the historical development of with respect to multidisciplinary aspects using association rule mining (ARM). ARM is a rule-based machine-learning approach tailored to identify validated relations among multiple variables in a large dataset. This study collected author keywords from all -related literature in the Web of Science database and examined the changes in validated -related topics using ARM. We found that -related research tends to diversify and expand over time. Although topics and their academic fields related to engineering and complex adaptive systems were prominent in the early 2000s, and have received significant attention in recent years. The increasing interest in -related topics linked to psychological and ecological factors, as well as social system components, can be attributed to the impact of a series of complex and global events that occurred in the late 2000s. Recently, has been conceived as a way of thinking, perspective, or paradigm to address emergent complexity and uncertainty with vague concepts. is increasingly being regarded as a boundary spanner that promotes communication and collaboration among stakeholders who share different interests and scientific knowledge.
本研究使用关联规则挖掘（ARM）从多学科角度分析了[研究对象]的历史发展。ARM是一种基于规则的机器学习方法，旨在识别大型数据集中多个变量之间的有效关系。本研究从科学网数据库中所有与[研究对象]相关的文献中收集作者关键词，并使用ARM研究与[研究对象]相关的有效主题的变化。我们发现，与[研究对象]相关的研究随着时间的推移趋于多样化和扩展。尽管与工程和复杂自适应系统相关的主题及其学术领域在21世纪初很突出，但[研究对象1]和[研究对象2]近年来受到了广泛关注。与心理和生态因素以及社会系统组成部分相关的[研究对象]相关主题的兴趣增加，可归因于2000年代后期发生的一系列复杂全球事件的影响。最近，[研究对象]被视为一种用模糊概念应对突发复杂性和不确定性的思维方式、视角或范式。[研究对象]越来越被视为促进具有不同兴趣和科学知识的利益相关者之间沟通与合作的跨界工具。
