Multi-item Recommendation
Multi-Item Recommendation is a recommendation framework that, as a distinct approach within personalized recommendation systems, generates sets of multiple items simultaneously—rather than individual item suggestions—by modeling interdependencies among items to optimize collective relevance and user satisfaction.
23
Publications
647
Citations
77
Authors
47
Institutions
Publications per year
2017–2026
15
Parents
23
1–5 of 23
77
2
h-index
2
h-index
2
h-index
2
h-index
1
h-index
1–5 of 77
47
University of Antwerp
Antwerp, Belgium
2 h-index
2 publications
43 citations

Illinois Institute of Technology
Chicago, United States
2 h-index
2 publications
69 citations

University of Edinburgh
Edinburgh, United Kingdom
2 h-index
2 publications
43 citations

Beihang University
Beijing, China
2 h-index
2 publications
43 citations

Universidad Autónoma de Madrid
Madrid, Spain
1 h-index
3 publications
246 citations
Jain University
Bengaluru, India
1 h-index
1 publications
28 citations
Accra Technical University
Accra, Ghana
1 h-index
1 publications
30 citations

Birkbeck, University of London
London, United Kingdom
1 h-index
1 publications
15 citations
1–8 of 47
2 publications · 95 citations
2
h-index
1 publications · 15 citations
1
h-index
1 publications · 15 citations
1
h-index
1 publications · 15 citations
1
h-index
Conference · 1 publications · 18 citations
1
h-index
1–5