标题： 更好的推荐：通过LOC链接数据服务验证AI生成的主题术语 显示英文标题

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

摘要： 本文探讨了将人工智能生成的主题术语整合到图书馆编目中的方法，重点通过国会图书馆链接数据服务进行验证。 它考察了在国会图书馆主题标题系统下传统主题编目的挑战，包括低效性和编目积压问题。 虽然生成式人工智能在加快编目流程方面显示出潜力，但研究表明人工智能分配的主题标题存在显著的准确性限制。 本文提出了一种结合人工智能技术与通过LOC链接数据服务进行人工验证的混合方法，旨在提高图书馆编目实践中元数据创建的准确性、效率和整体质量。 显示英文摘要

摘要： 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.