Personalized Content Recommendation is a computational method that tailors educational resources to individual learners by analyzing their preferences, behaviors, and performance within a Personalized Learning Environment, distinguishing it from general recommendation systems through its adaptive, learner-specific modeling of knowledge acquisition goals.
282
Publications
17.2K
Citations
851
Authors
350
Institutions
Publications per year
2017–2026
131
Publications
282
The YouTube video recommendation system
James Davidson, Benjamin Liebald, Junning Liu et al. · 2010 · 1.2K citations
Regression-based latent factor models
Deepak Agarwal, Bee-Chung Chen · 2009 · 527 citations
1–5 of 282
Authors
851
- JJ
8
h-index
- ML
7
h-index
- YB
7
h-index
- AG
6
h-index
- MR
5
h-index
1–5 of 851
Institutions
350
Universidade de Vigo
Vigo, Spain
8 h-index
47 publications
1.7K citations
Brigham Young University
Provo, United States
6 h-index
10 publications
302 citations
National Cheng Kung University
Tainan City, Taiwan
6 h-index
15 publications
526 citations
Cochin University of Science and Technology
Ernakulam, India
6 h-index
14 publications
863 citations
Zhejiang University
Hangzhou, China
5 h-index
19 publications
1.4K citations
Hong Kong University of Science and Technology
Hong Kong, Hong Kong
4 h-index
7 publications
365 citations
University of Freiburg
Freiburg im Breisgau, Germany
4 h-index
5 publications
126 citations
Yahoo (United States)
Sunnyvale, United States
4 h-index
11 publications
2.6K citations
1–8 of 350
Venues
- IEEE Access
8 publications · 620 citations
8
h-index
- IEEE Transactions on Consumer Electronics
7 publications · 355 citations
7
h-index
- Multimedia Tools and Applications
6 publications · 202 citations
6
h-index
- Expert Systems with Applications
6 publications · 324 citations
6
h-index
- arXiv (Cornell University)
Repository · 5 publications · 130 citations
5
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1–5