Cross-context Recommendation
Cross-Context Recommendation is a type of context-aware recommendation approach that integrates and transfers knowledge across different contextual domains or settings to improve recommendation accuracy and adaptability by leveraging contextual information from sources beyond the target context.
34
Publications
1.9K
Citations
136
Authors
63
Institutions
Publications per year
2017–2026
20
Parents
34
Alex Beutel, Paul Covington, Sagar Jain et al. · 2018 · 323 citations · Full text
Towards latent context-aware recommendation systems
Moshe Unger, Ariel Bar, Bracha Shapira et al. · Knowledge-Based Systems · 2016 · 116 citations
1–5 of 34
136
2
h-index
2
h-index
1
h-index
1
h-index
1
h-index
1–5 of 136
63

University of Duisburg-Essen
Essen, Germany
2 h-index
5 publications
289 citations

University of Minnesota
Minneapolis, United States
2 h-index
2 publications
49 citations

Sun Yat-sen University
Guangzhou, China
2 h-index
8 publications
300 citations

Polytechnic University of Bari
Bari, Italy
1 h-index
2 publications
124 citations
Free University of Bozen-Bolzano
Bolzano, Italy
1 h-index
2 publications
26 citations
Universidade Federal Rural de Pernambuco
Recife, Brazil
1 h-index
1 publications
25 citations
Lebanese American University
Beirut, Lebanon
1 h-index
1 publications
22 citations

Zhejiang University
Hangzhou, China
1 h-index
1 publications
78 citations
1–8 of 63
3 publications · 96 citations
3
h-index
3 publications · 349 citations
3
h-index
3 publications · 162 citations
3
h-index
1 publications · 22 citations
1
h-index
1 publications · 65 citations
1
h-index
1–5