Abstract
In the construction industry under “Industry 4.0”, Natural Language Processing (NLP) has been widely used to process and analyze text data to achieve construction intelligence. However, there lacks a comprehensive review of NLP application in construction-related areas, raising bar of research entry and setting obstacles for the rapid development in this fields. Ninety one NLP-related research articles in construction-related fields were retrieved to conduct a scientometric analysis using CiteSpace and VOSViewer, and summarized from the perspectives of anchordatasets/data sources, technologies/tools, and applications and progress. The results show that data isolation causing non-reproducibility of research is one of the severe problems to be solved. Besides, pure NLP application studies will no longer meet the future industry development needs and more cross-modal interdisciplinary research based on the end-to-end pre-trained neural network model framework is needed. This study helps readers gain an in-depth understanding of the NLP application and development in construction.
| Original language | English |
|---|---|
| Article number | 104169 |
| Journal | Automation in Construction |
| Volume | 136 |
| Online published | 24 Feb 2022 |
| DOIs | |
| Publication status | Published - Apr 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Research Keywords
- Artificial intelligence
- Construction research
- Industry 4.0
- Natural language processing
- Scientometric analysis
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