Automatically Categorizing Construction Accident Narratives Using the Deep-Learning Model with a Class-Imbalance Treatment Technique-Reference-Cited by-同舟云学术

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Automatically Categorizing Construction Accident Narratives Using the Deep-Learning Model with a Class-Imbalance Treatment Technique

Published:2024-09 Issue:9 Volume:150 Page:
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Shuang Qing¹,Liu Xishan²^ORCID,Wang Zhaojing³^ORCID,Xu Xinxin⁴

Affiliation:

1. Associate Professor, School of Economics and Management, Beijing Jiaotong Univ., Beijing 100044, China.

2. Master’s Candidate, School of Economics and Management, Beijing Jiaotong Univ., Beijing 100044, China. ORCID: .

3. Associate Professor, School of Economics and Management, Beijing Jiaotong Univ., Beijing 100044, China (corresponding author). ORCID: .

4. Master’s Candidate, School of Economics and Management, Beijing Jiaotong Univ., Beijing 100044, China.

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JCEMD4.COENG-14515

Reference45 articles.

1. A critical review of text-based research in construction: Data source, analysis method, and implications

2. Relational Graph Convolutional Network for Text-Mining-Based Accident Causal Classification

3. Text mining-based construction site accident classification using hybrid supervised machine learning

4. Fatal Construction Accidents in Hong Kong

5. Incident Causation Model for Improving Feedback of Safety Knowledge

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