Contextual Preference Learning
Contextual Preference Learning is a machine learning framework that models user preferences as a function of contextual variables, distinguishing itself from general preference learning by explicitly incorporating situational, temporal, or environmental factors to adapt recommendations dynamically.
41
Publications
2.2K
Citations
121
Authors
54
Institutions
Publications per year
2017–2026
21
Parents
41
Bridging Collaborative Filtering and Semi-Supervised Learning
Carl Yang, Lanxiao Bai, Chao Zhang et al. · 2017 · 302 citations
Neural Personalized Ranking for Image Recommendation
Wei Niu, James Caverlee, Haokai Lu · 2018 · 127 citations
1–5 of 41
121
2
h-index
2
h-index
University of California, Los Angeles, United States
2 publications · 127 citations
2
h-index
2
h-index
2
h-index
1–5 of 121
54
University of California, Los Angeles
Los Angeles, United States
3 h-index
6 publications
399 citations
University of Science and Technology of China
Hefei, China
2 h-index
4 publications
426 citations
Politecnico di Milano
Milan, Italy
2 h-index
7 publications
261 citations

Zhejiang University
Hangzhou, China
2 h-index
7 publications
141 citations
University of Illinois Urbana-Champaign
Urbana, United States
2 h-index
7 publications
1.7K citations

Xi'an Jiaotong University
Xi'an, China
2 h-index
8 publications
1.3K citations
Rutgers, The State University of New Jersey
New Brunswick, United States
1 h-index
1 publications
162 citations

Middlesex University
London, United Kingdom
1 h-index
3 publications
48 citations
1–8 of 54
TKDE · 2 publications · 251 citations
2
h-index
1 publications · 14 citations
1
h-index
1 publications · 10 citations
1
h-index
1 publications · 16 citations
1
h-index
1 publications · 106 citations
1
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1–5