ADHO Digital Humanities Conference 2023 (DH2023)
Published June 30, 2023 | Version v1
Poster Open

Modeling Prototypicality and Uncertainty in Genre Concepts

Creators

  • 1. Ludwig-Maximilians-Universität München

Contributors

  • 1. University of Graz
  • 2. Belgrade Center for Digital Humanities
  • 3. Le Mans Université
  • 4. Digital Humanities im deutschsprachigen Raum

Description

The poster develops and discusses a new technique of modeling prototypicality in genre concepts based on the c@1-score as an uncertainty-based accuracy score and perspectival modeling within the framework of supervised machine learning. The technique is intended to provide better understanding of loosely ordered genres.

Files

Schroeter_Modeling-Prototypicality-and-Uncertainty-in-Genre-Concepts.pdf

Files (581.0 kB)

Additional details

Related works

Is supplement to
Conference paper: 10.5281/zenodo.8107640 (DOI)