Dashboard Recommender Systems
Dashboard Recommender System is a computational framework that autonomously suggests dashboard configurations or visualizations by analyzing user intent, data characteristics, and design best practices within the context of interactive data visualization.
6
Publications
176
Citations
24
Authors
11
Institutions
Publications per year
2017–2026
6
Parents
6
DMiner: Dashboard Design Mining and Recommendation
Yanna Lin, Haotian Li, Aoyu Wu et al. · IEEE Transactions on Visualization and Computer Graphics · 2023 · 25 citations · Full text
Computing, Design, Visualization +15
1–5 of 6
11

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
2 h-index
6 publications
206 citations
Université de Tours
Tours, France
1 h-index
4 publications
80 citations
KU Leuven
Leuven, Belgium
1 h-index
3 publications
75 citations
Northeastern University
Boston, United States
1 h-index
1 publications
28 citations
Universidad de Salamanca
Salamanca, Spain
1 h-index
3 publications
75 citations
Centre Hospitalier de Roubaix
Roubaix, France
1 h-index
1 publications
20 citations
Université de Lille
Lille, France
1 h-index
1 publications
20 citations
Microsoft (United States)
Redmond, United States
1 h-index
6 publications
318 citations
1–8 of 11
TVCG · 3 publications · 106 citations
3
h-index
1 publications · 25 citations
1
h-index
1 publications · 20 citations
1
h-index
1–3