AIDA-Vis – Automatic Data Visualization with Human Preferences
Autor(en):
Zusammenfassung
Data visualization is a complex task that typically requires human expertise, acquired through a large number of professional working hours. The automatic generation of reasonable visualizations would be a good solution for inexperienced laypeople. However, existing approaches fall short since they are quite static and rely only on traditional supervised learning. This results in models which recommend a single visualization solely based on the dataset features. User preferences and goals are not taken into account. We propose a more flexible solution that is iteratively updated with the individual user's preferences and outputs a ranked list of visualizations for a given dataset.
- Vollständige Referenz
- BibTeX
Laurito, Wa., Höllig, Ja., Lachowitzer, Jo., Thoma, St., Budde, Ma. & Philipp, Pa.,
(2022).
AIDA-Vis – Automatic Data Visualization with Human Preferences.
In:
Demmler, D., Krupka, D. & Federrath, H.
(Hrsg.),
INFORMATIK 2022.
Gesellschaft für Informatik, Bonn.
(S. 301-305).
DOI: 10.18420/inf2022_27
@inproceedings{mci/Laurito2022,
author = {Laurito,Walter AND Höllig,Jacqueline AND Lachowitzer,Jonas AND Thoma,Steffen AND Budde,Matthias AND Philipp,Patrick},
title = {AIDA-Vis – Automatic Data Visualization with Human Preferences},
booktitle = {INFORMATIK 2022},
year = {2022},
editor = {Demmler, Daniel AND Krupka, Daniel AND Federrath, Hannes} ,
pages = { 301-305 } ,
doi = { 10.18420/inf2022_27 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
author = {Laurito,Walter AND Höllig,Jacqueline AND Lachowitzer,Jonas AND Thoma,Steffen AND Budde,Matthias AND Philipp,Patrick},
title = {AIDA-Vis – Automatic Data Visualization with Human Preferences},
booktitle = {INFORMATIK 2022},
year = {2022},
editor = {Demmler, Daniel AND Krupka, Daniel AND Federrath, Hannes} ,
pages = { 301-305 } ,
doi = { 10.18420/inf2022_27 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
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Mehr Information
DOI: 10.18420/inf2022_27
ISBN: 978-3-88579-720-3
ISSN: 1617-5468
Datum: 2022
Sprache:
(en)
(en)
