There have been growing uses of semantic networks in the past decade, such as leveraging large-scale pre-trained graph knowledge databases for various natural language processing (NLP) tasks in engineering design research. Therefore, the paper provides a survey of the research that has employed semantic networks in the engineering design research community. The survey reveals that engineering design researchers have primarily relied on WordNet, ConceptNet, and other common-sense semantic network databases trained on non-engineering data sources to develop methods or tools for engineering design. Meanwhile, there are emerging efforts to mine large scale technical publication and patent databases to construct engineering-contextualized semantic network databases, e.g., B-Link and TechNet, to support NLP in engineering design. On this basis, we recommend future research directions for the construction and applications of engineering-related semantic networks in engineering design research and practice.

中文翻译：

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工程设计语义网：一项调查

在过去的十年中，语义网络的使用不断增长，例如在工程设计研究中利用大规模的预训练图知识数据库来完成各种自然语言处理（NLP）任务。因此，本文提供了对在工程设计研究社区中采用语义网络的研究的概述。调查显示，工程设计研究人员主要依靠WordNet，ConceptNet和其他在非工程数据源上受过训练的常识语义网络数据库来开发工程设计方法或工具。同时，正在出现新的努力来挖掘大规模的技术出版物和专利数据库，以构建工程环境下的语义网络数据库，例如B-Link和TechNet，以支持NLP进行工程设计。在此基础上，