Cataloger acceptance and use of semiautomated subject recommendations for web scale linked data systems

作者
Jim Hahn
出版者
International Federation of Library Associations and Institutions (IFLA)
出版日期
2022 June 20
內容

As catalogers begin to integrate linked data descriptions into large-scale discovery graphs through RDF editors, interventions such as semi-automated subject description (http://lcsh.annif.info) are extending and supporting their professional expertise. A large corpus of 9.3 million (9,304,455) title and subject pairs from the IvyPlus Platform for Open Data (POD), along with SVDE bibliographic data, were used for training a semi-automated subject indexing tool for use in BIBFRAME linked data editors. Thereafter, catalogers evaluated the automated subject outputs for inclusion in their descriptions of BIBFRAME resources and the general usefulness of semi-automated subject suggestions. This paper presents the findings of a mixed-methods inquiry to better understand catalogers’ preferences for incorporating machine learning outputs into their work.

刊名
87th IFLA World Library and Information Congress (WLIC) / 2022 in Dublin, Ireland
關鍵字
Linked Data, Machine Learning, Big Data, Metadata, Ethics
網址連結
發布日期:2022年07月13日 最後更新:2022年07月28日