AI-enhanced reference services in special libraries: a case study of the Hakka Literary Museum.

Purpose: This study explores integrating artificial intelligence (AI) technologies into reference services within special libraries, focusing on the Hakka Literary Museum as a case example. It aims to address the limitations of traditional reference services in meeting complex and domain-specific in...

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Publicado en:Electronic Library Vol. 43; no. 5; pp. 715 - 733
Autores principales: Chen, Chao-Chen, Chang, Chen-Chi
Formato: case study tables/charts Journal Article
Publicado: Emerald Publishing Limited 2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2025
      vid: 43
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      pub: Emerald Publishing Limited
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        189668885
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        189668885
        10.1108/EL-05-2025-0168
        189668885
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        atl: AI-enhanced reference services in special libraries: a case study of the Hakka Literary Museum.
      aug:
        au:
          Chen, Chao-Chen
          Chang, Chen-Chi
        affil: College of Humanities and Education, Center of General Education, Chung Yuan Christian University, Taoyuan City, Taiwan
      sug:
        subj:
          Artificial Intelligence
          Library Reference Services
          Libraries, Special
          Information Technology
          Conceptual Framework
          Information Retrieval
          Museums
          Library Services
          Natural Language Processing
          Libraries, Electronic
          Culture
          Access to Information
          Consumer Satisfaction
          User-Computer Interface
          Organizational Efficiency
          Quality Improvement
          Library Automation
          Information Services
          Programming Languages
      ab: Purpose: This study explores integrating artificial intelligence (AI) technologies into reference services within special libraries, focusing on the Hakka Literary Museum as a case example. It aims to address the limitations of traditional reference services in meeting complex and domain-specific information needs, especially under constraints of limited human resources. Design/methodology/approach: A case study methodology examines the layered implementation of AI technologies, including retrieval-augmented generation (RAG) and GraphRAG. These tools support four tiers of reference services: directive reference via real-time Web scraping, conceptual reference using RAG for topic-specific responses, deep-indexing through iterative document expansion and thematic reference via GraphRAG-powered hierarchical knowledge graphs. Each layer is tailored to support varying depths of user inquiry. Findings: This study finds that AI-enhanced reference services significantly improve service responsiveness, content depth and user satisfaction in cultural and special library settings. The system enables accurate and efficient responses to both basic and advanced inquiries, bridging gaps in human resource availability and enabling continuous access to cultural knowledge resources. Originality/value: This research contributes to the growing literature on AI in information services by offering a practical model for implementing multilayered reference assistance in special libraries. It highlights the novel use of GraphRAG for cultural knowledge mapping and demonstrates how AI can support the preservation and dissemination of intangible heritage. The study also provides insights into the transformative role of AI in redefining user experience and operational efficiency in information services.
      pubtype: Academic Journal
      doctype:
        case study
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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