【摘要】 我国许多地区蕴含着丰富的文化资源，其文旅信息涵盖了跨多学科的人文、自然和考古知识.依赖传统的导游和领域专家难以全面解答游客的文旅问题，而经典的基于关键词检索和匹配的知识问答系统在处理如此广泛且复杂的知识时显得力不从心.这为游客获取全面的文旅知识，提升文化体验带来了挑战.为此，提出了一种基于知识图谱与大语言模型的文旅知识智能整合方法.该方法通过大语言模型自动抽取文旅领域的实体和关系，从而构建出一个具备紧密关联的文旅知识图谱.在此图谱的基础上，对大语言模型进行定向检索和生成增强，以获得更全面和精准的文旅问题解答.本文以文化底蕴深厚的良渚地区为应用对象，构建了智能问答系统.结果表明，该方法能够更加有效地整合多领域的文旅知识，并提供高质量的文旅问题解答.更多还原

【Abstract】 Many regions in China are rich in cultural heritage, with cultural and tourism information spanning interdisciplinary knowledge from the humanities, nature, and archaeology.Relying on traditional tour guides and domain experts is insufficient for comprehensively addressing tourists’ cultural and tourism queries, and classic keyword-based retrieval and matching knowledge Q&A systems struggle to manage such extensive and complex knowledge effectively.This presents significant challenges for tourists seeking comprehensive cultural tourism knowledge and enhancind cultural experiences.To tackle this issue, this paper proposes an intelligent integration method for cultural and tourism knowledge based on knowledge graphs and large language models(CTK-KG).This method employs large language models to automatically extract entities and relationships within the cultural and tourism domain, constructing a tightly connected cultural and tourism knowledge graph.Based on this graph, the language model is enhanced with targeted retrieval and generation capabilities to provide more comprehensive and accurate answers to cultural and tourism questions.Using the culturally rich Liangzhu region as an application example, an intelligent Q&A system is developed.Experimental results demonstrate that this method effectively integrates multi-domain cultural and tourism knowledge and provides high-quality answers to cultural and tourism questions.更多还原