Journalartikel - Wissenschaftlicher Artikel | 2023 | Peer reviewed

Predicting Rating Distributions of Website Aesthetics with Deep Learning for AI-Based Research

Autor*innen

Eisbach, Simon ; Daugs, Fabian ; Thielsch, Meinald T. ; Böhmer, Matthias ; Hertel, Guido

Zeitschrift

ACM transactions on computer human interaction

DOI

10.1145/3569889

URL

https://dl.acm.org/doi/pdf/10.1145/3569889

Weitere Details

Sprache

englisch

Darstellungsform

Text

Band

Ausgabe

Artikelnummer

Schlüsselwörter

Deep Learning, Aesthetics Prediction, Website Aesthetics

Zitierstile

Eisbach, S., Daugs, F., Thielsch, M. T., Böhmer, M., & Hertel, G. (2023). Predicting Rating Distributions of Website Aesthetics with Deep Learning for AI-Based Research. ACM Transactions on Computer Human Interaction, 30(3), 37. doi:10.1145/3569889

In die Zwischenablage kopieren

Eisbach, S., Daugs, F., Thielsch, M.T., Böhmer, M. and Hertel, G., 2023. Predicting Rating Distributions of Website Aesthetics with Deep Learning for AI-Based Research. ACM transactions on computer human interaction, [online] 30(3), p.37. Available at: <https://dl.acm.org/doi/pdf/10.1145/3569889>.

In die Zwischenablage kopieren

Eisbach, Simon u. a. 2023. Predicting Rating Distributions of Website Aesthetics with Deep Learning for AI-Based Research. ACM transactions on computer human interaction 30, 3, 37. https://dl.acm.org/doi/pdf/10.1145/3569889.

American Psychological Association 6th edition (DOI)

Anglia Ruskin University - Harvard

Gesellschaft für Bildung und Forschung in Europa - Harvard