Hybrid Factorization Models
Hybrid Factorization Models is a recommendation system model that integrates multiple factorization techniques—such as matrix factorization, tensor factorization, or deep factorization—within a unified framework to jointly capture diverse interaction patterns and auxiliary information, thereby improving predictive performance beyond single-factorization approaches.
29
Publications
1.3K
Citations
129
Authors
64
Institutions
Publications per year
2017–2026
18
Parents
29
FedRec: Federated Recommendation With Explicit Feedback
Guanyu Lin, Feng Liang, Weike Pan et al. · IEEE Intelligent Systems · 2020 · 207 citations
Peng Cui, Fei Wang, Shaowei Liu et al. · 2011 · 130 citations
Computing, Data Science, Data Mining +15
Collaborative Filtering for Recommender Systems
Ruisheng Zhang, Qi-dong Liu, Chun-Gui et al. · 2014 · 123 citations
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Tsinghua University
Beijing, China
3 h-index
9 publications
970 citations
Sobolev Institute of Mathematics
Novosibirsk, Russia
2 h-index
2 publications
92 citations
Istituto Nazionale di Fisica Nucleare
Rome, Italy
2 h-index
5 publications
229 citations
Fondazione Bruno Kessler
Trento, Italy
2 h-index
3 publications
137 citations

Sun Yat-sen University
Guangzhou, China
2 h-index
5 publications
561 citations
European Centre for Theoretical Studies in Nuclear Physics and Related Areas
Trento, Italy
2 h-index
3 publications
137 citations

University of Calabria
Rende, Italy
2 h-index
5 publications
229 citations
Istituto Nazionale di Fisica Nucleare, Trento Institute for Fundamental Physics And Applications
Povo, Italy
2 h-index
3 publications
137 citations
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1 publications · 27 citations
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1 publications · 18 citations
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FGCS · 1 publications · 245 citations
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JHEP · 1 publications · 20 citations
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1 publications · 12 citations
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