Document (#43727)

Author
Hahn, J.
Title
Semi-automated methods for BIBFRAME work entity description
Source
Cataloging and classification quarterly. 59(2021) no.8, p.853-867
Year
2021
Abstract
This paper reports an investigation of machine learning methods for the semi-automated creation of a BIBFRAME Work entity description within the RDF linked data editor Sinopia (https://sinopia.io). The automated subject indexing software Annif was configured with the Library of Congress Subject Headings (LCSH) vocabulary from the Linked Data Service at https://id.loc.gov/. The training corpus was comprised of 9.3 million titles and LCSH linked data references from the IvyPlus POD project (https://pod.stanford.edu/) and from Share-VDE (https://wiki.share-vde.org). Semi-automated processes were explored to support and extend, not replace, professional expertise.
Content
Vgl.: https://doi.org/10.1080/01639374.2021.2014011.
Footnote
Teil eines Themenheftes: Artificial intelligence (AI) and automated processes for subject sccess
Theme
Formalerschließung
Object
BIBFRAME

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