The pressure on systems engineering is ever-increasing to support the development and implementation of systems that meet a complex environment's demands. As a growing discipline, systems engineering requires insight into past research to identify opportunities for future growth. Analyzing the bibliometric data on published research provides valuable information on a scientific discipline's past progress and future prospects. Therefore, this paper extracts the research topics published in INCOSE's journal Systems Engineering and the annual international symposium proceedings to analyze their composition and allocation to papers. The implemented process applies natural language processing and topic modeling to extract the main topics from these papers' titles and abstracts. Analyzing these research topics' composition and mapping them to processed articles helps to understand their relative importance. The analysis's output confirms the importance of modeling in systems engineering, as it is the most popular topic. The additional focus of research papers on the systems engineering process, practice, and methodologies also indicates that the field is still growing and evolving. Some important topics to systems engineering, which were not found as prominent topics, are humans' roles in systems, verification and validation, and other specialty fields. This new knowledge about the structure of research into systems engineering can identify future research project opportunities to continue growing the field.

中文翻译：

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INCOSE Systems Engineering期刊及国际研讨会研究课题分析

为了支持满足复杂环境需求的系统的开发和实施，系统工程的压力不断增加。作为一门不断发展的学科，系统工程需要深入了解过去的研究，以确定未来发展的机会。分析已发表研究的文献计量数据可提供有关科学学科过去进展和未来前景的宝贵信息。因此，本文摘录了INCOSE旗下期刊Systems Engineering发表的研究课题以及年度国际研讨会论文集，以分析其构成和论文分配。实施过程应用自然语言处理和主题建模从这些论文的标题和摘要中提取主要主题。分析这些研究主题的组成并将它们映射到处理过的文章有助于了解它们的相对重要性。分析的输出证实了建模在系统工程中的重要性，因为它是最受欢迎的话题。对系统工程过程、实践和方法论的研究论文的额外关注也表明该领域仍在发展和发展。系统工程的一些重要主题（未被发现为突出主题）是人类在系统、验证和确认以及其他专业领域中的角色。