Hybrid Matrix Factorization
Hybrid Matrix Factorization is a matrix factorization-based recommendation technique that integrates multiple sources of information or collaborative signals—such as content, context, or social data—through hybridization strategies to improve prediction accuracy beyond traditional factorization methods.
29
Publications
1.7K
Citations
105
Authors
47
Institutions
Publications per year
2017–2026
15
Parents
29
Dual Channel Hypergraph Collaborative Filtering
Shuyi Ji, Yifan Feng, Rongrong Ji et al. · 2020 · 215 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
1–5 of 29
105
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2 publications · 164 citations
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47
Tsinghua University
Beijing, China
4 h-index
12 publications
1.6K citations
University of Oxford
Oxford, United Kingdom
2 h-index
3 publications
108 citations
Oxford Centre for Mission Studies
Oxford, United Kingdom
1 h-index
1 publications
86 citations

Xi'an Polytechnic University
Xi'an, China
1 h-index
1 publications
10 citations
University of Copenhagen
Copenhagen, Denmark
1 h-index
5 publications
545 citations
Arizona State University
Tempe, United States
1 h-index
1 publications
245 citations

Hebei University of Technology
Tianjin, China
1 h-index
3 publications
33 citations

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
1 h-index
3 publications
162 citations
1–8 of 47
1 publications · 22 citations
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Repository · 1 publications · 80 citations
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1 publications · 18 citations
1
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IJBIDM · 1 publications · 24 citations
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FGCS · 1 publications · 245 citations
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