基于大模型的人因工程实验教学知识图谱构建方法研究

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中图分类号：TP391.1 文献标识码：A 文章编号：2096-4706（2026）06-0161-08

Research on Knowledge Graph Construction Methods for Human Factors Engineering Experimental Teaching Based on LLMs

YAO Yanzi， YAN Jingbin （DepartmentofIndustrialEngineering，TsinghuaUniversity，Beijingooo84，China）

Abstract：Toaddressthecomplexity，resource fragmentation，and weak logical structure inhuman factors engieering experimental teaching，this study proposes a method for constructing a knowledge graph for human factors engineering experimental teaching based on Large Language Models （LLMs）.Byconstructing a standardized corpus for human factors enginering，designingtheconceptualnodesandaknowledgeontology，andfine-tuningtheGLM-4-Flashmodel，theacurate semanticaalysisof human factors experimental design is finallachieved.Meanwhile，the Neo4j graph databaseis used to dynamicallyconstruct theKnowledge Graphto lower the barrertoknowledgeleaming.Theinnovationofthis study lies in thefirst-timein-depth integrationofLLM-basedsemanticunderstandinganddynamicgraphconstructioninthefieldofhuman factors engineering experimental teaching，providinga salable technicalsolution forthe intellectualizationof human factors engineering experimental teaching.

Keywords： human factors engineering; experimental teaching; Knowledge Graph; Neo4j graph database

0 引言

人因工程（Human Factors Engineering，HFE）是一门融合心理学、工程学、计算机科学等多领域理论方法的综合性交叉学科，致力于通过识别人类能力、局限和行为，并将其应用于系统设计，以确保系统的安全性、舒适性和效率[1。（剩余10965字）