---
_id: '6954'
article_number: '3719'
article_type: review
author:
- first_name: Arne
  full_name: Tillmann, Arne
  last_name: Tillmann
- first_name: Anton
  full_name: Thielmann, Anton
  last_name: Thielmann
- first_name: Gillian
  full_name: Kant, Gillian
  last_name: Kant
- first_name: Christoph
  full_name: Weisser, Christoph
  id: '264138'
  last_name: Weisser
  orcid: 0000-0003-0616-1027
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0003-0616-1027/work/216453482
- first_name: Benjamin
  full_name: Säfken, Benjamin
  last_name: Säfken
- first_name: Alexander
  full_name: Silbersdorff, Alexander
  last_name: Silbersdorff
- first_name: Thomas
  full_name: Kneib, Thomas
  last_name: Kneib
citation:
  alphadin: '<span style="font-variant:small-caps;">Tillmann, Arne</span> ; <span
    style="font-variant:small-caps;">Thielmann, Anton</span> ; <span style="font-variant:small-caps;">Kant,
    Gillian</span> ; <span style="font-variant:small-caps;">Weisser, Christoph</span>
    ; <span style="font-variant:small-caps;">Säfken, Benjamin</span> ; <span style="font-variant:small-caps;">Silbersdorff,
    Alexander</span> ; <span style="font-variant:small-caps;">Kneib, Thomas</span>:
    AuDoLab: Automatic Document Labeling and Classification for Extremely Unbalanced
    Data. In: <i>Journal of Open Source Software</i> Bd. 6, Open Journals (2021),
    Nr. 66'
  ama: 'Tillmann A, Thielmann A, Kant G, et al. AuDoLab: Automatic Document Labeling
    and Classification for Extremely Unbalanced Data. <i>Journal of Open Source Software</i>.
    2021;6(66). doi:<a href="https://doi.org/10.21105/joss.03719">10.21105/joss.03719</a>'
  apa: 'Tillmann, A., Thielmann, A., Kant, G., Weisser, C., Säfken, B., Silbersdorff,
    A., &#38; Kneib, T. (2021). AuDoLab: Automatic Document Labeling and Classification
    for Extremely Unbalanced Data. <i>Journal of Open Source Software</i>, <i>6</i>(66).
    <a href="https://doi.org/10.21105/joss.03719">https://doi.org/10.21105/joss.03719</a>'
  bibtex: '@article{Tillmann_Thielmann_Kant_Weisser_Säfken_Silbersdorff_Kneib_2021,
    title={AuDoLab: Automatic Document Labeling and Classification for Extremely Unbalanced
    Data}, volume={6}, DOI={<a href="https://doi.org/10.21105/joss.03719">10.21105/joss.03719</a>},
    number={663719}, journal={Journal of Open Source Software}, publisher={Open Journals},
    author={Tillmann, Arne and Thielmann, Anton and Kant, Gillian and Weisser, Christoph
    and Säfken, Benjamin and Silbersdorff, Alexander and Kneib, Thomas}, year={2021}
    }'
  chicago: 'Tillmann, Arne, Anton Thielmann, Gillian Kant, Christoph Weisser, Benjamin
    Säfken, Alexander Silbersdorff, and Thomas Kneib. “AuDoLab: Automatic Document
    Labeling and Classification for Extremely Unbalanced Data.” <i>Journal of Open
    Source Software</i> 6, no. 66 (2021). <a href="https://doi.org/10.21105/joss.03719">https://doi.org/10.21105/joss.03719</a>.'
  ieee: 'A. Tillmann <i>et al.</i>, “AuDoLab: Automatic Document Labeling and Classification
    for Extremely Unbalanced Data,” <i>Journal of Open Source Software</i>, vol. 6,
    no. 66, 2021.'
  mla: 'Tillmann, Arne, et al. “AuDoLab: Automatic Document Labeling and Classification
    for Extremely Unbalanced Data.” <i>Journal of Open Source Software</i>, vol. 6,
    no. 66, 3719, Open Journals, 2021, doi:<a href="https://doi.org/10.21105/joss.03719">10.21105/joss.03719</a>.'
  short: A. Tillmann, A. Thielmann, G. Kant, C. Weisser, B. Säfken, A. Silbersdorff,
    T. Kneib, Journal of Open Source Software 6 (2021).
date_created: 2026-06-01T14:01:39Z
date_updated: 2026-06-02T05:45:14Z
doi: 10.21105/joss.03719
intvolume: '         6'
issue: '66'
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
publication: Journal of Open Source Software
publication_identifier:
  eissn:
  - 2475-9066
publication_status: published
publisher: Open Journals
quality_controlled: '1'
status: public
title: 'AuDoLab: Automatic Document Labeling and Classification for Extremely Unbalanced
  Data'
type: journal_article
user_id: '220548'
volume: 6
year: '2021'
...