Using Text Mining and Bayesian Network to Identify Key Risk Factors for Safety Accidents in Metro Construction-Reference-Cited by-同舟云学术

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Using Text Mining and Bayesian Network to Identify Key Risk Factors for Safety Accidents in Metro Construction

Published:2024-06 Issue:6 Volume:150 Page:
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Shen Jianhong¹^ORCID,Liu Shupeng²^ORCID,Zhang Jing³

Affiliation:

1. Professor, School of Management Engineering, Qingdao Univ. of Technology, Qingdao 266520, China. ORCID: .

2. Graduate Student, School of Management Engineering, Qingdao Univ. of Technology, Qingdao 266520, China (corresponding author). ORCID: .

3. Graduate Student, School of Management Engineering, Qingdao Univ. of Technology, Qingdao 266520, China.

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JCEMD4.COENG-14114

Reference73 articles.

1. AFP (Agence France Presse). 2008. “21 dead in China subway accident: State media—eb247—News—Asia—Emirates24|7.” Accessed January 10 2023. https://www.emirates247.com/eb247/news/asia/21-dead-in-china-subway-accident-state-media-2008-11-19-1.227244.

2. Text mining of accident reports using semi-supervised keyword extraction and topic modeling

3. Unsupervised Machine Learning for Managing Safety Accidents in Railway Stations

4. Advanced uncertainty modelling for container port risk analysis

5. Injury severity on traffic crashes: A text mining with an interpretable machine-learning approach

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