中国中医药图书情报杂志2026，Vol.50Issue(5)：32-38,7.DOI:10.3969/j.issn.2095-5707.202508085
融合大语言模型与知识图谱的绍派伤寒智能问答系统构建研究
Study on Intelligent Question-answering System for Shao School of Cold-induced Disease Based on Large Language Models and Knowledge Graph
摘要
Abstract
Objective To construct an intelligent question-answering system for Shao School of cold-induced disease by integrating large language models(LLMs)and knowledge graph(KG)technology.Methods Utilizing medical cases of Shao School of cold-induced disease as the data source,an LLMs-based approach was implemented to automatically extract entities and relationships contained in medical cases of Shao School of cold-induced disease,thereby constructing a multi-dimensional knowledge graph hierarchically mapped around the core axes of"disease-pattern-symptom-cause-treatment-herb".A semantic mapping-based,two-stage query transformation mechanism was proposed to convert natural language queries into precise Cypher graph queries.Concurrently,the retrieved graph data were transformed into coherent,professional standardized natural language answers.Results The newly constructed knowledge graph of Shao School of cold-induced disease contained 10 entity types,3 711 nodes,10 relationship types and 14 940 edges,with standardized storage achieved via Neo4j graph database.Expert evaluation demonstrated that the developed intelligent question-answering system achieved a comprehensive score of 85.02,significantly outperforming the standalone LLMs(82.04)and the direct KG query results(59.46).Conclusion The developed intelligent question-answering system of Shao School of cold-induced disease enables efficient knowledge retrieval and generates highly professional and interpretable answers.This framework effectively promotes the digital and intelligent preservation and innovation of the academic system of Shao School of cold-induced disease,offering references for the construction ideas of other intelligent clinical diagnosis and treatment systems.关键词
绍派伤寒/大语言模型/知识图谱/智能问答系统Key words
Shao School of cold-induced disease/large language model/knowledge graph/intelligent question-answering system分类
医药卫生引用本文复制引用
金海心,吴毅晗,何素珍,张越,赵佳璐..融合大语言模型与知识图谱的绍派伤寒智能问答系统构建研究[J].中国中医药图书情报杂志,2026,50(5):32-38,7.基金项目
国家级大学生创新创业训练计划(202410344004) （202410344004）
浙江中医药大学校级科研基金(2023JKJNTS23) （2023JKJNTS23）
