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Using AI to Auto-Tag Graduate Theses.

This article presents a practical approach to using artificial intelligence (AI) for tagging graduate theses in an institutional repository with the United Nations Sustainable Development Goals. Utilizing strategies requiring no prior programming experience, the article provides a step-by-step guide...

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Publicado en:Information Technology & Libraries Vol. 44; no. 4; pp. 1 - 11
Autor principal: Morgan, Kyle
Formato: Journal Article
Publicado: American Library Association Dec2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2025
      vid: 44
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      pub: American Library Association
      place: Chicago, Illinois
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        atl: Using AI to Auto-Tag Graduate Theses.
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        au: Morgan, Kyle
        affil: Scholarly Communications and Digital Scholarship Librarian, Cal Poly Humboldt
      sug:
        subj:
          Artificial Intelligence
          Theses and Dissertations
          United Nations
          Sustainable Growth
          Data Mining
          Librarianship
          Information Storage
          Information Retrieval
          Metadata
          Natural Language Processing
          Benchmarking
          Cost Benefit Analysis
          Workflow
      ab: This article presents a practical approach to using artificial intelligence (AI) for tagging graduate theses in an institutional repository with the United Nations Sustainable Development Goals. Utilizing strategies requiring no prior programming experience, the article provides a step-by-step guide, cost analysis, and lessons learned from employing two AI-based tagging methods. These methods, attempted with varying degrees of success, highlight the real potential of using AI for the thematic tagging of digital library resources.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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