The objective of this study is to construct and analyze a knowledge graph based on construction accident case data with the aim of enhancing the efficiency of information exploration and analysis. By meticulously organizing and graphically representing accident case data, the study devises a methodology for automated knowledge graph construction employing cutting-edge AI models and tools. The research automates data processing to handle the increasing data volume, with 23,877 accident cases from the Construction Safety Information (CSI) system. The knowledge graph clarifies complex data relationships, thereby enabling in-depth analysis of the causes of accidents and the formulation of preventive strategies. The study's key findings demonstrate the knowledge graph's ability to visualize semantic relationships, enhance decision-making efficiency, and enhance construction site safety by reducing accident frequency.
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Lee et al. (2024) studied this question.
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