User Preference Inference
User Preference Inference is a computational methodology within implicit feedback modeling that derives latent user preferences from observable interaction behaviors by distinguishing underlying preference signals from noise and confounding factors inherent in implicit data.
147
Publications
9.7K
Citations
566
Authors
202
Institutions
Publications per year
2017–2026
87
Parents
147
Attentive Collaborative Filtering
Jingyuan Chen, Hanwang Zhang, Xiangnan He et al. · 2017 · 876 citations
Automatic identification of user interest for personalized search
Feng Qiu, Junghoo Cho · 2006 · 399 citations
Learning Tree-based Deep Model for Recommender Systems
Zhu Han, Xiang Li, Pengye Zhang et al. · 2018 · 291 citations · Full text
Shilad Sen, Jesse Vig, John Riedl · 2009 · 282 citations
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National University of Singapore
Singapore, Singapore
8 h-index
17 publications
4.6K citations
Shandong University
Jinan, China
8 h-index
21 publications
2.2K citations
Tsinghua University
Beijing, China
6 h-index
18 publications
1.5K citations
University of Science and Technology of China
Hefei, China
6 h-index
14 publications
1K citations
Nanyang Technological University
Singapore, Singapore
6 h-index
13 publications
626 citations
Tencent (China)
Shenzhen, China
6 h-index
14 publications
1.8K citations

Shanghai Jiao Tong University
Shanghai, China
5 h-index
12 publications
1.2K citations
Columbia University
New York, United States
4 h-index
5 publications
1.2K citations
1–8 of 202
Conference · 5 publications · 244 citations
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5 publications · 116 citations
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Repository · 5 publications · 175 citations
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Conference · 5 publications · 242 citations
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4 publications · 83 citations
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