A Correlation Analysis of Construction Site Fall Accidents Based on Text Mining
Author(s): |
Xixi Luo
Quanlong Liu Zunxiang Qiu |
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Medium: | journal article |
Language(s): | English |
Published in: | Frontiers in Built Environment, January 2021, v. 7 |
DOI: | 10.3389/fbuil.2021.690071 |
Abstract: |
Construction site fall accidents are a high-frequency accident type in the construction industry and have received extensive attention from accident causal factor analysis and risk management research, but evaluating the relationship between accident causal factors and unstructured texts remains an area in urgent need of further study. In this paper, an analysis method based on text mining was chosen to analyze and process the collected data of 557 investigation reports of construction site fall accidents in China from 2013 to 2019. First, the accident reports were preprocessed to identify six types and 28 causal factors of fall accidents; subsequently, the 28 causal factors were classified into critical causal factors, subcritical causal factors and general causal factors according to their document frequency. Then, the Apriori algorithm was used to analyze the correlation of construction site fall accidents. Finally, strong association rules were obtained between the accident causal factors and between the causal factors and the types of construction site fall accidents. The results showed that |
Copyright: | © Xixi Luo, Quanlong Liu, Zunxiang Qiu |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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10614244 - Published on:
09/07/2021 - Last updated on:
14/09/2021