Search (8 results, page 1 of 1)

  • × year_i:[2020 TO 2030}
  • × theme_ss:"Automatisches Indexieren"
  1. Pintscher, L.; Bourgonje, P.; Moreno Schneider, J.; Ostendorff, M.; Rehm, G.: Wissensbasen für die automatische Erschließung und ihre Qualität am Beispiel von Wikidata : die Inhaltserschließungspolitik der Deutschen Nationalbibliothek (2021) 0.01
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    Source
    Qualität in der Inhaltserschließung. Hrsg.: M. Franke-Maier, u.a
  2. Franke-Maier, M.; Beck, C.; Kasprzik, A.; Maas, J.F.; Pielmeier, S.; Wiesenmüller, H: ¬Ein Feuerwerk an Algorithmen und der Startschuss zur Bildung eines Kompetenznetzwerks für maschinelle Erschließung : Bericht zur Fachtagung Netzwerk maschinelle Erschließung an der Deutschen Nationalbibliothek am 10. und 11. Oktober 2019 (2020) 0.00
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  3. Junger, U.; Scholze, F.: Neue Wege und Qualitäten : die Inhaltserschließungspolitik der Deutschen Nationalbibliothek (2021) 0.00
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    Source
    Qualität in der Inhaltserschließung. Hrsg.: M. Franke-Maier, u.a
  4. Sack, H.: Hybride Künstliche Intelligenz in der automatisierten Inhaltserschließung (2021) 0.00
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    Source
    Qualität in der Inhaltserschließung. Hrsg.: M. Franke-Maier, u.a
  5. Lowe, D.B.; Dollinger, I.; Koster, T.; Herbert, B.E.: Text mining for type of research classification (2021) 0.00
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    Abstract
    This project brought together undergraduate students in Computer Science with librarians to mine abstracts of articles from the Texas A&M University Libraries' institutional repository, OAKTrust, in order to probe the creation of new metadata to improve discovery and use. The mining operation task consisted simply of classifying the articles into two categories of research type: basic research ("for understanding," "curiosity-based," or "knowledge-based") and applied research ("use-based"). These categories are fundamental especially for funders but are also important to researchers. The mining-to-classification steps took several iterations, but ultimately, we achieved good results with the toolkit BERT (Bidirectional Encoder Representations from Transformers). The project and its workflows represent a preview of what may lie ahead in the future of crafting metadata using text mining techniques to enhance discoverability.
  6. Asula, M.; Makke, J.; Freienthal, L.; Kuulmets, H.-A.; Sirel, R.: Kratt: developing an automatic subject indexing tool for the National Library of Estonia : how to transfer metadata information among work cluster members (2021) 0.00
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  7. Qualität in der Inhaltserschließung (2021) 0.00
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    Editor
    Franke-Maier, M., A. Kasprzik, A. Ledl u. H. Schürmann
    Type
    m
  8. Ahmed, M.: Automatic indexing for agriculture : designing a framework by deploying Agrovoc, Agris and Annif (2023) 0.00
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