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Better Recommendations: Validating AI-generated Subject Terms Through LOC Linked Data Service

Year: 2025

Type: preprint

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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2508.00867

Authors: Tang, Kwok Leong, Jiang, Yi

Institutions: Harvard University, Indiana University Bloomington, Indiana University

Language: English

Topic: Library Science and Information Systems

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4417161960

Cites:

Cited by: 4

Related to: 10