Better Recommendations: Validating AI-generated Subject Terms Through LOC Linked Data Service
July 18, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Kwok Leong Tang, Yi Jiang
arXiv ID
2508.00867
Category
cs.DL: Digital Libraries
Cross-listed
cs.AI,
cs.IR
Citations
0
Venue
arXiv.org
Last Checked
3 months ago
Abstract
This article explores the integration of AI-generated subject terms into library cataloging, focusing on validation through the Library of Congress Linked Data Service. It examines the challenges of traditional subject cataloging under the Library of Congress Subject Headings system, including inefficiencies and cataloging backlogs. While generative AI shows promise in expediting cataloging workflows, studies reveal significant limitations in the accuracy of AI-assigned subject headings. The article proposes a hybrid approach combining AI technology with human validation through LOC Linked Data Service, aiming to enhance the precision, efficiency, and overall quality of metadata creation in library cataloging practices.
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