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Identifying convergence fields and technologies for industrial safety: LDA-based network analysis

机译:确定工业安全的融合领域和技术:基于LDA的网络分析

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摘要

As industrial systems expand and complex systems are developed, it is no longer effective to minimize hazards and risks for industrial safety using the technological solutions limited to a single industry. Thus, to resolve complicated problems, safety technology has been developed by promoting technology innovation and convergence. In this respect, this study aims at monitoring major safety fields and technologies through patent analysis to identify the trends in technology development that prevent the risks of various industrial systems. Patent information is effectively used for analyzing technology descriptions, which include the purpose and newness of technology. Using this patent information, we propose the major safety fields and related technology keywords using the following two techniques: (1) latent Dirichlet allocation (LDA), which aims to extract the latent topics and main keywords contained in documents, and (2) network analysis, which is useful for monitoring change patterns and relations. Further, the convergence trajectories of safety technology are identified to provide insights about the technology trends in safety fields. The results are expected to enable safety managers and engineers to effectively find relevant technology trends for reducing hazardous factors.
机译:随着工业系统的扩展和复杂系统的开发,使用仅限于单个行业的技术解决方案来最小化对工业安全的危害和风险已不再有效。因此,为了解决复杂的问题,已经通过促进技术创新和融合来开发安全技术。在这方面,本研究旨在通过专利分析来监控主要的安全领域和技术,以识别防止各种工业系统风险的技术发展趋势。专利信息可有效地用于分析技术描述,其中包括技术的目的和新颖性。利用此专利信息,我们使用以下两种技术提出了主要的安全领域和相关技术关键字:(1)潜在的狄利克雷分配(LDA),旨在提取文档中包含的潜在主题和主要关键字,以及(2)网络分析,对于监视变更模式和关系很有用。此外,确定安全技术的融合轨迹以提供有关安全领域技术趋势的见解。预期结果将使安全管理人员和工程师能够有效地找到相关的技术趋势,以减少危险因素。

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