User Preference Modeling
User Preference Modeling is a computational framework that formalizes the acquisition, representation, and adaptation of individual or collective user preferences within recommendation systems by integrating behavioral, contextual, and multi-criteria data to enable personalized and group-aware adaptive user interfaces.
1.8K
Publications
96.2K
Citations
5K
Authors
1.2K
Institutions
Publications per year
2017–2026
784
1.8K
Latent semantic models for collaborative filtering
Thomas Hofmann · ACM Transactions on Information Systems · 2004 · 1.4K citations
Exploiting geographical influence for collaborative point-of-interest recommendation
Mao Ye, Peifeng Yin, Wang-Chien Lee et al. · 2011 · 1.1K citations
Computing, Data Science, Data Mining +11
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University of Science and Technology of China
Hefei, China
32 h-index
94 publications
5.8K citations
National University of Singapore
Singapore, Singapore
31 h-index
95 publications
8.8K citations
Tsinghua University
Beijing, China
27 h-index
129 publications
5.9K citations

University of Minnesota
Minneapolis, United States
23 h-index
70 publications
7.8K citations
Nanyang Technological University
Singapore, Singapore
20 h-index
54 publications
3.4K citations
Carnegie Mellon University
Pittsburgh, United States
20 h-index
34 publications
2.5K citations

Shanghai Jiao Tong University
Shanghai, China
19 h-index
73 publications
3.4K citations
University of Technology Sydney
Sydney, Australia
19 h-index
50 publications
2.8K citations
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43 publications · 2.4K citations
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TKDE · 32 publications · 2.3K citations
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27 publications · 2.8K citations
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28 publications · 919 citations
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Repository · 33 publications · 1.4K citations
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