图书情报工作

图书情报工作 >

2025 , Vol. 69 >Issue 21: 108 - 119

DOI: https://doi.org/10.13266/j.issn.0252-3116.2025.21.009

研究论文

检索增强思维在图书馆知识挖掘服务中的应用研究

  • 郭利敏 ,
  • 付雅明 ,
  • 刘悦如
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  • 1 上海图书馆/上海科学技术情报研究所 上海 200031;
    2 上海大学文化遗产与信息管理学院 上海 200444;
    3 同济大学图书馆 上海 200092
郭利敏，副研究馆员，硕士；付雅明，助理研究员，博士，通信作者，E-mail：ymingfu@126.com；刘悦如，副研究馆员，硕士。

收稿日期: 2024-10-15

  修回日期: 2024-12-17

  网络出版日期: 2025-11-11

基金资助

本文系上海市白玉兰人才计划浦江项目“基于生成式人工智能的文化遗产知识服务研究”(项目编号:24PJC036); 上海市哲学社会科学项目“智慧数据驱动的大都市图书馆科研创新支撑服务”(项目编号:2020BTQ005)研究成果之一。

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Research on the Application of Retrieval Augmented Thoughts in Library Knowledge Mining Services

  • Guo Limin ,
  • Fu Yaming ,
  • Liu Yueru
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  • 1 Shanghai Library/Institute of Scientific & Technical Information of Shanghai, Shanghai 200031;
    2 School of Cultural Heritage and Information Management, Shanghai University, Shanghai 200444;
    3 Tongji University Library, Shanghai 200092
Guo Limin, Associate Research Librarian, Master’s Degree; Fu Yaming, Assistant Researcher, PhD, Corresponding Author, E-mail: ymingfu@126.com; Liu Yueru, Associate Research Librarian, Master’s Degree.

Received date: 2024-10-15

  Revised date: 2024-12-17

  Online published: 2025-11-11

Supported by

This work is supported by Shanghai Magnolia Talent Program Pujiang Project titled “Research on Cultural Heritage Knowledge Service Based on Generative Artificial Intelligence”(Grant No. 24PJC036);the Philosophy and Social Sciences of Shanghai Project titled “Smart DataDriven Research Innovation Support Services in Metropolitan Libraries”(Grant No. 2020BTQ005).

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摘要

[目的/意义] 聚焦大语言模型时代图书馆知识挖掘服务的发展现状，探索结合传统检索方法和检索增强思维，为用户提供既深刻又逻辑严密的知识信息，旨在提升图书馆的知识服务水平。[方法/过程] 采用实验研究方法，以上海图书馆人名规范库为数据源，重点挖掘与宋代茶文化相关的信息，目标是从馆藏数据中揭示更多关于这一时期茶文化的细节，为用户提供更加全面和深入的视角。[结果/结论] 实验结果表明，检索增强思维方法在图书馆知识挖掘服务中具有一定优势。该方法不仅有助于提高数据挖掘的效率和准确性，还能为图书馆知识挖掘服务提供新的技术解决方案，对智慧图书馆的建设具有参考价值。

关键词： 知识挖掘; 检索增强思维; 智慧图书馆服务; 大语言模型

本文引用格式

郭利敏 , 付雅明 , 刘悦如 . 检索增强思维在图书馆知识挖掘服务中的应用研究[J]. 图书情报工作, 2025 , 69(21) : 108 -119 . DOI: 10.13266/j.issn.0252-3116.2025.21.009

Abstract

[Purpose/Significance] The study focuses on the development of library knowledge mining services in the era of large language models. It explores the integration of traditional retrieval methods with retrieval augmented thoughts（RAT） to provide users with both profound and logically rigorous knowledge information, aiming to enhance the quality of library knowledge services. [Method/Process] The study adopted an experimental research approach, taking the Name Authority Database of Shanghai Library as the data source. It specifically focused on mining information related to tea culture in Song Dynasty, uncovering more details about this historical period from library collections, thus offering users a more comprehensive and in-depth perspective. [Result/Conclusion] Experimental results indicate that the RAT method has certain advantages in library knowledge mining services. This approach not only improves the efficiency and accuracy of data mining but also provides new technical solutions for library knowledge mining, offering valuable insights for the development of smart libraries.

Key words： knowledge mining; retrieval augmented thoughts（RAT）; smart library services; large language models

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