Data Linking Workshop 2023: Computer Vision and Natural Language Processing – Challenges in the Humanities

Link:
Autor/in:
Verlag/Körperschaft:
Universität Hamburg
Erscheinungsjahr:
2023
Medientyp:
Text
Schlagworte:
  • UWA
  • CSMC
  • Data Linking
  • RFF
  • AI
  • Natural Language Processing
  • NLP
  • Computer Vision
  • CV
  • CHAI
  • Humanities
  • Indology
Beschreibung:
  • The humanities meet computer science to create new synergies using computer vision and natural language processing.

    Aim & Scope

    Historians are increasingly using technologies to evaluate digitised texts in a machine-readable way, as well as techniques from the field of natural language processing (NLP) to analyse the content and context of language in written artefacts. These techniques can be used to analyse large corpora and identify patterns. In general, however, these methods often use training data from current rather than historical data. The use of these methods can lead to biases in the historical record, incurring the risk of false inferences about history. Therefore, the methods used should be fully investigated to account for any biases. In this DL workshop, the challenges of applying computer vision and NLP techniques in the humanities, and first solutions to them, will be presented.

    This entry includes the following presentations from the first Data Linking Workshop 2023: Computer Vision and Natural Language Processing – Challenges in the Humanities

     

  • The workshop was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy - EXC 2176 'Understanding Written Artefacts: Material, Interaction and Transmission in Manuscript Cultures', project no. 390893796.
relatedIdentifier:
DOI 10.25592/uhhfdm.10769 DOI 10.25592/uhhfdm.9672 DOI 10.25592/uhhfdm.12923
Lizenzen:
  • https://creativecommons.org/licenses/by/4.0/legalcode
  • info:eu-repo/semantics/openAccess
Quellsystem:
Forschungsdatenrepositorium der UHH

Interne Metadaten
Quelldatensatz
oai:fdr.uni-hamburg.de:13099