Semantic Networks for Engineering Design: A Survey
arXiv:2012.07060 · doi:10.1017/pds.2021.523
Abstract
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.
arXiv comment12 pages, 2 tables, conference
References in corpus (8)
- Efficient Estimation of Word Representations in Vector Space
- Language Models are Few-Shot Learners
- XLNet: Generalized Autoregressive Pretraining for Language Understanding
- ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
- ConceptNet 5.5: An Open Multilingual Graph of General Knowledge
- TechNet: Technology Semantic Network Based on Patent Data
- Guiding Data-Driven Design Ideation by Knowledge Distance
- Enhancing user creativity: Semantic measures for idea generation
Cited by in corpus (6)
- Stopwords in Technical Language Processing
- Data-Driven Design-by-Analogy: State of the Art and Future Directions
- Opportunities for Large Language Models and Discourse in Engineering Design
- Quantitative dynamics of design thinking and creativity perspectives in company context
- Engineering Knowledge Graph from Patent Database
- Dynamic semantic networks for exploration of creative thinking