情报科学 ›› 2024, Vol. 42 ›› Issue (12): 130-140.

• 业务研究 • 上一篇    下一篇

基于大语言模型的高校图书馆传统文化阅读推广的知识图谱构 建及优化路径

  

  • 出版日期:2024-12-05 发布日期:2025-06-27

  • Online:2024-12-05 Published:2025-06-27

摘要: 【目的/意义】在新时代背景下,探索基于大语言模型的高校图书馆传统文化阅读推广的知识图谱构建流 程,通过可视化图谱优化阅读推广路径,推动传统文化资源的深度挖掘与系统化组织,创新高校图书馆的阅读推广 模式。【方法/过程】本研究提出一种基于大语言模型的传统文化阅读推广内容的知识图谱构建流程,采集数据后先 进行数据清洗处理,运用 BERTopic主题模型提取实体类别与关系标签,再使用 deepseek-r1大语言模型进行实体 抽取与关系识别,最后将实体关系三元组导入Neo4j图数据库,以实现知识图谱的可视化展示。此外并利用百度搜 索以及微信搜一搜平台中的具体内容构建高校图书馆传统文化阅读推广知识图谱,探讨其在传统文化阅读推广中 的创新路径模式。【结果/结论】研究结果表明:基于deepseek-r1模型的知识图谱构建方法能够清晰呈现传统文化阅 读推广中的组织机构、活动形式及推广策略等,形成结构化的知识表达体系;进一步分析传统文化阅读推广知识内 容,可辅助传统文化阅读案例库建设,助力构建智能化问答系统,协助挖掘传统文化阅读推广路径,以发挥高校图 书馆文化传承的阵地作用。【创新/局限】提出了一种基于大语言模型的传统文化阅读推广内容的知识图谱构建方 法,并挖掘知识元素用于高校图书馆传统文化推广,但由于计算机资源的限制,未来的研究中可以借助第三方平台 的大模型接口。

Abstract: 【Purpose/significance】In the context of the new era, to explore the knowledge graph construction process of traditional cul⁃ ture reading promotion in college libraries based on the big language model, to optimize the reading promotion path through the visual graph, to promote the deep excavation and systematic organization of traditional culture resources, and to innovate the reading promo⁃ tion mode in college libraries.【Method/process】This study proposes a knowledge graph construction process of traditional culture reading promotion content based on large language model. After collecting data, we first carry out data cleaning and processing, use BERTopic topic model to extract entity categories and relationship labels, and then use deepseek-r1 large language model for entity extraction and relationship recognition, and finally import the entity relationship triples into Neo4j graph database, which can be used to optimize the reading promotion path through visual graph. Finally, the entity-relationship triples are imported into the Neo4j graph database to achieve the visualization of the knowledge graph. In addition, we use the specific content of Baidu search and WeChat search platform to construct the knowledge map of traditional culture reading promotion in college libraries, and explore its innovative path mode in traditional culture reading promotion.【Result/conclusion】The results of the study show that the knowledge mapping method based on the deepseek-r1 model can clearly present the organization, activities and promotion strategies in traditional culture reading promotion, forming a structured knowledge expression system; further analysis of the knowledge content of traditional culture reading promotion can assist in the construction of the traditional culture reading case base, help build an intelligent Q&A system, as⁃ sist in the mining of traditional culture reading promotion paths, and assist in the construction of the traditional culture reading case base, and assist in the construction of the traditional culture reading case base. mining traditional culture reading promotion paths, in order to play the role of the position of cultural heritage in college libraries.【Innovation/limitation】A knowledge graph construction method of traditional culture reading promotion content based on big language model is proposed, and the knowledge elements are mined for traditional culture promotion in college libraries, but due to the limitation of computer resources, the big model interface of the third-party platform can be used in the future research.