Exploration of Latent Themes in Truck-Mounted Attenuator (TMA) Related Accidents Using Natural Language Processing-Reference-Cited by-同舟云学术

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Exploration of Latent Themes in Truck-Mounted Attenuator (TMA) Related Accidents Using Natural Language Processing

Published:2024-01-25 Issue: Volume:101 Page:218-225
ISSN:
Container-title:Computing in Civil Engineering 2023
language:
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Author:

Tian Chi¹¹¹¹²,Wu Hongyue¹¹¹¹²,Chen Yunfeng¹¹¹¹²,Zhang Jiansong¹¹¹¹²,Feng Yiheng¹¹¹¹²

Affiliation:

1. School of Construction Management Technology, Purdue Univ., West Lafayette, IN

2. Lyles School of Civil Engineering, Purdue Univ., West Lafayette, IN

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784485224.027

Reference18 articles.

1. Natural Language Processing

2. Incident Causation Model for Improving Feedback of Safety Knowledge;Chua D. K. H.;Journal of Construction Engineering and Management,2004

3. Hardeniya, N. (2015). NLTK essentials : build cool NLP and machine learning applications using NLTK and other Python libraries. Packt Publishing Ltd., Birmingham, UK.

4. Trajectory optimization of connected and autonomous vehicles at a multilane freeway merging area;Hu X.;Transportation Research Part C: Emerging Technologies,2019

5. Indiana Department of Transportation. (2018). Work Zone Safety. Retrieved on March 25th 2023 https://www.in.gov/indot/safety/work-zone-safety/.

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