User Preference Protection
User Preference Protection is a privacy-preserving mechanism in recommendation systems that specifically safeguards the confidentiality and integrity of individual users' behavioral and declarative preference data against unauthorized inference or reconstruction during model training and inference.
100
Publications
4.4K
Citations
311
Authors
155
Institutions
Publications per year
2017–2026
45
100
Privacy-enhanced personalization
Alfred Kobsa · Communications of the ACM · 2007 · 211 citations · Full text
SVD-based collaborative filtering with privacy
Hüseyin Polat, Wenliang Du · 2005 · 210 citations
P3P: making privacy policies more useful
Lorrie Faith Cranor · IEEE Security & Privacy · 2003 · 180 citations
1–5 of 100
311
8
h-index
4
h-index
3
h-index
Nanjing University of Information Science and Technology, China
3 publications · 132 citations
3
h-index
3
h-index
1–5 of 311
155

Anadolu University
Eskişehir, Türkiye
6 h-index
13 publications
315 citations
Nanjing University
Nanjing, China
5 h-index
10 publications
390 citations
Eskişehir City Hospital
Eskişehir, Turkey
5 h-index
11 publications
281 citations

Nanjing University of Information Science and Technology
Nanjing, China
4 h-index
6 publications
399 citations

Tel Aviv University
Tel Aviv, Israel
3 h-index
4 publications
127 citations

Macquarie University
Sydney, Australia
3 h-index
4 publications
119 citations
University of Technology Sydney
Sydney, Australia
3 h-index
3 publications
89 citations
Syracuse University
Syracuse, United States
3 h-index
6 publications
712 citations
1–8 of 155
Conference · 3 publications · 114 citations
3
h-index
TKDE · 3 publications · 367 citations
3
h-index
3 publications · 68 citations
3
h-index
3 publications · 140 citations
3
h-index
FGCS · 3 publications · 142 citations
3
h-index
1–5