Trust-aware Matrix Factorization
Trust-Aware Matrix Factorization is a matrix factorization-based recommendation method that incorporates user trust relationships into the latent factor model to enhance prediction accuracy by jointly modeling user-item interactions and user-to-user trust propagation.
20
Publications
5.2K
Citations
77
Authors
49
Institutions
Publications per year
2017–2026
12
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Recommender systems with social regularization
Hao Ma, Dengyong Zhou, Chao Liu et al. · 2011 · 1.7K citations
Learning to recommend with trust and distrust relationships
Hao Ma, Michael R. Lyu, Irwin King · 2009 · 211 citations
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49
University of Technology Sydney
Sydney, Australia
3 h-index
4 publications
515 citations
Dalian University of Technology
Dalian, China
3 h-index
5 publications
164 citations
Hosei University
Tokyo, Japan
2 h-index
4 publications
170 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
2 h-index
5 publications
3.9K citations
Zhejiang University of Science and Technology
Hangzhou, China
2 h-index
6 publications
700 citations
Simon Fraser University
Burnaby, Canada
1 h-index
2 publications
3.3K citations

Xi'an Polytechnic University
Xi'an, China
1 h-index
1 publications
19 citations

Zhejiang University of Technology
Hangzhou, China
1 h-index
1 publications
55 citations
1–8 of 49
2 publications · 32 citations
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Conference · 1 publications · 23 citations
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1 publications · 71 citations
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1 publications · 312 citations
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1 publications · 19 citations
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