Ensemble Recommendation is a hybrid recommendation approach that combines multiple base recommenders through strategic integration mechanisms to improve predictive accuracy and robustness beyond the capabilities of individual constituent models.
148
Publications
9.5K
Citations
476
Authors
217
Institutions
Publications per year
2017–2026
88
Parents
Publications
148
1–5 of 148
Authors
476
- MG
7
h-index
- PB
4
h-index
- IC
4
h-index
- DJ
3
h-index
- LR
3
h-index
1–5 of 476
Institutions
217
Universidade de São Paulo
São Paulo, Brazil
6 h-index
21 publications
442 citations
Universidad Autónoma de Madrid
Madrid, Spain
6 h-index
10 publications
753 citations
University of Minnesota
Minneapolis, United States
5 h-index
7 publications
1.8K citations
University of Klagenfurt
Klagenfurt, Austria
3 h-index
3 publications
382 citations
Ben-Gurion University of the Negev
Beersheba, Israel
3 h-index
11 publications
266 citations
University of Pittsburgh
Pittsburgh, United States
3 h-index
4 publications
635 citations
Tsinghua University
Beijing, China
3 h-index
5 publications
291 citations
Yanshan University
Qinhuangdao, China
3 h-index
6 publications
132 citations
1–8 of 217
Venues
- Expert Systems with Applications
10 publications · 379 citations
10
h-index
- Knowledge-Based Systems
7 publications · 520 citations
7
h-index
- Information Sciences
5 publications · 166 citations
5
h-index
- Applied Soft Computing
4 publications · 420 citations
4
h-index
- Multimedia Tools and Applications
3 publications · 109 citations
3
h-index
1–5