AI Chatbots and Subject Cataloging: A Performance Test

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Detaylı Bibliyografya
Yayımlandı:Library Resources & Technical Services vol. 69, no. 2 (Apr 2025)
Yazar: Dobreski, Brian
Diğer Yazarlar: Hastings, Christopher
Baskı/Yayın Bilgisi:
American Library Association
Konular:
Online Erişim:Citation/Abstract
Full Text - PDF
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100 1 |a Dobreski, Brian 
245 1 |a AI Chatbots and Subject Cataloging: A Performance Test 
260 |b American Library Association  |c Apr 2025 
513 |a Feature 
520 3 |a Libraries show an increasing interest in incorporating AI tools into their workflows, particularlyeasily accessible and free-to-use chatbots. However, empirical evidence is limited regarding theeffectiveness of these tools to perform traditionally time-consuming subject cataloging tasks. In thisstudy, researchers sought to assess the performance of AI tools in performing basic subject headingand classification number assignment. Using a well-established instructional cataloging text as abasis, researchers developed and administered a test designed to evaluate the effectiveness of three chatbots (ChatGPT, Gemini, Copilot) in assigning Dewey Decimal Classification, Library of Congress Classification, and Library of Congress Subject Heading terms and numbers. The quantity and quality of errors in chatbot responses were analyzed. 
653 |a Classification 
653 |a Artificial intelligence 
653 |a Chatbots 
653 |a Performance tests 
653 |a Effectiveness 
653 |a Libraries 
653 |a Human-computer interaction 
653 |a Cataloging 
653 |a Errors 
653 |a Researcher subject relations 
653 |a Task performance 
653 |a Legislatures 
653 |a Text structure 
700 1 |a Hastings, Christopher 
773 0 |t Library Resources & Technical Services  |g vol. 69, no. 2 (Apr 2025) 
786 0 |d ProQuest  |t Library Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3201918295/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3201918295/fulltextPDF/embedded/H09TXR3UUZB2ISDL?source=fedsrch