基于大模型的人因工程实验教学知识图谱构建方法研究OA

To address the complexity,resource fragmentation,and weak logical structure in human factors engineering experimental teaching,this study proposes a method for constructing a knowledge graph for human factors engineering experimental teaching based on Large Language Models(LLMs).By constructing a standardized corpus for human factors engineering,designing the conceptual nodes and a knowledge ontology,and fine-tuning the GLM-4-Flash model,the accurate semantic analysis of human factors experimental design is finally achieved.Meanwhile,the Neo4j graph database is used to dynamically construct the Knowledge Graph to lower the barrier to knowledge learning.The innovation of this study lies in the first-time in-depth integration of LLM-based semantic understanding and dynamic graph construction in the field of human factors engineering experimental teaching,providing a scalable technical solution for the intellectualization of human factors engineering experimental teaching.