Skip to main navigation Skip to search Skip to main content

Designing Experts’ Interactions with a Semi-Automated Document Tagging System

  • Sebastian Müller (Speaker)
  • , Beat Tödtli
  • , Janine Vetsch
  • , Melanie Rickenmann
  • , Simon Haug
  • , Matthias Baldauf
  • , Peter Fröhlich
  • Eastern Switzerland University of Applied Sciences

Research output: Chapter in Book or Conference ProceedingsConference Proceedings with Oral Presentationpeer-review

Abstract

For evidence-based care, nurses are dependent on latest scientific findings. However, screening and annotating respective publications is a time-consuming process for domain experts. In our ongoing work, we investigate how such experts can be supported by a (semi-)automated, machine-learning based recommendation system and how to design and integrate such a tool into their overall workflow. This paper outlines a current tag recommendation prototype and presents first results from an initial co-design workshop where we investigated the requirements of two nursing care researchers for such a system. The mockups created during the workshops lay the foundation for our goal of integrating a recommender system seamlessly into the researchers annotation process.
Original languageEnglish
Title of host publicationProceedings of the Workshop on Engaging with Automation co-located with the ACM Conference on Human Factors in Computing Systems (CHI 2022)
Pages1-5
Number of pages5
Publication statusPublished - 2022
EventCHI 2022: ACM CHI Conference on Human Factors in Computing Systems -
Duration: 30 Apr 20226 May 2022

Conference

ConferenceCHI 2022: ACM CHI Conference on Human Factors in Computing Systems
Period30/04/226/05/22

Research Field

  • Former Research Field - Capturing Experience

Keywords

  • 2. Quartal 2022

Fingerprint

Dive into the research topics of 'Designing Experts’ Interactions with a Semi-Automated Document Tagging System'. Together they form a unique fingerprint.

Cite this