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Automatically learning construction injury precursors from text

https://doi.org/10.1016/j.autcon.2020.103145

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Automated content analysis for construction safety: A natural language processing system to extract precursors and outcomes from unstructured injury reports

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Application of machine learning to construction injury prediction

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Retrieving similar cases for construction project risk management using Natural Language Processing techniques

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Text analytics to analyze and monitor construction project contract and correspondence

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Construction site accident analysis using text mining and natural language processing techniques

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Accident Case Retrieval and Analyses: Using Natural Language Processing in the Construction Industry

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Hierarchical Attention Networks for Document Classification

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Deep Contextualized Word Representations

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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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Convolutional Neural Networks for Sentence Classification

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Word Embeddings for the Construction Domain

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inferred← citeshttps://doi.org/10.18653/v1/2020.acl-main.603openalex-snapshot

Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension

inferred← citeshttps://doi.org/10.2139/ssrn.4804307openalex-snapshot

Improving Large Language Model Assisted Categorization and Classification of Highway Construction Accidents from Osha Databases

inferred← citeshttps://doi.org/10.2139/ssrn.6532324openalex-snapshot

An integrated GNN-LLM framework for automated task-level safety risk assessment leveraging retrieval-augmented scenario generation

inferred← citeshttps://doi.org/10.29007/snfnopenalex-snapshot

Unravelling Safety Concerns in Construction: A Comprehensive Data Analysis

inferred← citeshttps://doi.org/10.3233/wor-220533openalex-snapshot

Construction accident prevention: A systematic review of machine learning approaches

inferred← citeshttps://doi.org/10.32738/jeppm-2024-0014openalex-snapshot

Enhancing Construction Site Safety: Natural Language Processing for Hazards Identification and Prevention

inferred← citeshttps://doi.org/10.3389/fbuil.2026.1815172openalex-snapshot

Text mining and natural language processing in construction research: a scientometric analysis and qualitative review

inferred← citeshttps://doi.org/10.3389/fpsyg.2022.886390openalex-snapshot

Study on Influencing Factors of Construction Workers’ Unsafe Behavior Based on Text Mining

inferred← citeshttps://doi.org/10.3389/fpubh.2022.984099openalex-snapshot

Predicting occupational injury causal factors using text-based analytics: A systematic review

inferred← citeshttps://doi.org/10.3390/app14020664openalex-snapshot

Harnessing Generative Pre-Trained Transformers for Construction Accident Prediction with Saliency Visualization

inferred← citeshttps://doi.org/10.3390/buildings11120583openalex-snapshot

Exploring Natural Language Processing in Construction and Integration with Building Information Modeling: A Scientometric Analysis

inferred← citeshttps://doi.org/10.3390/buildings13020345openalex-snapshot

Determining Critical Cause Combination of Fatality Accidents on Construction Sites with Machine Learning Techniques

inferred← citeshttps://doi.org/10.3390/buildings13122933openalex-snapshot

Identification of Occupant Dissatisfaction Factors in Newly Constructed Apartments: Text Mining and Semantic Network Analysis

inferred← citeshttps://doi.org/10.3390/buildings14061797openalex-snapshot

Development of a Site Information Classification Model and a Similar-Site Accident Retrieval Model for Construction Using the KLUE-BERT Model

inferred← citeshttps://doi.org/10.3390/buildings15142410openalex-snapshot

GPT Applications for Construction Safety: A Use Case Analysis

inferred← citeshttps://doi.org/10.3390/buildings15173063openalex-snapshot

A Novel Method for Named Entity Recognition in Long-Text Safety Accident Reports of Prefabricated Construction

inferred← citeshttps://doi.org/10.3390/buildings16204029openalex-snapshot

Explainable Emergency Response Recommendation for Foundation Pit Collapse Accidents: An LLM-Enabled E/B/R Ontology-Driven Hybrid Reasoning Framework

inferred← citeshttps://doi.org/10.3390/informatics9020043openalex-snapshot

Advancements in Artificial Intelligence-Based Decision Support Systems for Improving Construction Project Sustainability: A Systematic Literature Review

inferred← citeshttps://doi.org/10.3390/risks9010007openalex-snapshot

Mining Actuarial Risk Predictors in Accident Descriptions Using Recurrent Neural Networks

inferred← citeshttps://doi.org/10.3390/safety9020022openalex-snapshot

A Scoping Literature Review of Natural Language Processing Application to Safety Occurrence Reports

inferred← citeshttps://doi.org/10.3390/su132413579openalex-snapshot

Current Status and Future Directions of Deep Learning Applications for Safety Management in Construction

inferred← citeshttps://doi.org/10.3390/su142416846openalex-snapshot

Text Mining Applications in the Construction Industry: Current Status, Research Gaps, and Prospects

inferred← citeshttps://doi.org/10.3390/su17104454openalex-snapshot

Achieving Sustainable Construction Safety Management: The Shift from Compliance to Intelligence via BIM–AI Convergence

inferred← citeshttps://doi.org/10.36253/10.36253/979-12-215-0289-3.76openalex-snapshot

Extracting Information from Construction Safety Requirements Using Large Language Model

inferred← citeshttps://doi.org/10.36680/j.itcon.2022.045openalex-snapshot

Machine learning-based automated classification of worker-reported safety reports in construction

inferred← citeshttps://doi.org/10.36680/j.itcon.2024.045openalex-snapshot

Leveraging large language models for enhanced construction safety regulation extraction

inferred← citeshttps://doi.org/10.36680/j.itcon.2025.019openalex-snapshot

A review of machine learning for analysing accident reports in the construction industry

inferred← citeshttps://doi.org/10.36750/2524-2555.81.89-97openalex-snapshot

CONCEPTUAL FOUNDATIONS FOR THE INTEGRATION OF LOGISTICS PROCESSES OF CONSTRUCTION ENTERPRISES INTO THE EUROPEAN MANAGEMENT STANDARDS SYSTEM

inferred← citeshttps://doi.org/10.3850/978-981-18-8071-1_p233-cdopenalex-snapshot

Human Factor Identification in Aviation Accidents Using Contextual Word Embeddings

inferred← citeshttps://doi.org/10.66573/001c.89002openalex-snapshot

Framework of BERT-Based NLP Models for Frequency and Severity in Insurance Claims

inferred← citeshttps://doi.org/10.7717/peerj-cs.1985openalex-snapshot

Contextualizing injury severity from occupational accident reports using an optimized deep learning prediction model

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