Content Recommendation Analysis
Content Recommendation Analysis is a scholarly analytical framework that systematically evaluates the effectiveness, relevance, and performance of algorithms or models designed to suggest digital content to users based on behavioral, contextual, or semantic criteria.
10
Publications
464
Citations
22
Authors
16
Institutions
Publications per year
2017–2026
7
Parents
10
22
2
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 22
16
Indian Institute of Technology Kharagpur
Kharagpur, India
2 h-index
5 publications
206 citations
Max Planck Institute for Software Systems
Saarbrücken, Germany
2 h-index
4 publications
162 citations
Universidade Federal de Minas Gerais
Belo Horizonte, Brazil
2 h-index
3 publications
124 citations
Tokyo Metropolitan University
Tokyo, Japan
1 h-index
1 publications
13 citations
Samsung (South Korea)
Seoul, South Korea
1 h-index
1 publications
16 citations
Max Planck Society
Munich, Germany
1 h-index
3 publications
120 citations

Kyoto University
Kyoto, Japan
1 h-index
1 publications
13 citations

ITMO University
St Petersburg, Russia
1 h-index
2 publications
48 citations
1–8 of 16
JCMC · 1 publications · 43 citations
1
h-index
1 publications · 230 citations
1
h-index
1 publications · 21 citations
1
h-index
1 publications · 16 citations
1
h-index
1 publications · 12 citations
1
h-index
1–5