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Fast and Accurate Non-Negative Latent Factor Analysis of High-Dimensional and Sparse Matrices in Recommender Systems
Xin Luo
, Yue Zhou
, Zhigang Liu
,
Mengchu Zhou
Electrical and Computer Engineering
Research output
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Contribution to journal
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Article
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peer-review
127
Scopus citations
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Dive into the research topics of 'Fast and Accurate Non-Negative Latent Factor Analysis of High-Dimensional and Sparse Matrices in Recommender Systems'. Together they form a unique fingerprint.
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Keyphrases
Recommender Systems
100%
Sparse Matrices
100%
High-dimensional Matrices
100%
Non-negative Latent Factor Analysis
100%
Fast Convergence
75%
Non-negative Latent Factor Model
50%
Theoretical Proof
50%
Industrial Application
25%
Latent Factors
25%
Matrix Analysis
25%
Momentum Coefficient
25%
Discrete-time Case
25%
Mathematics
Sparse Matrix
100%
Factor Analysis
100%
Latent Factor
100%
Multiplicative
25%
Discrete Time
25%
Continuous Time
25%
Time Case
25%
Computer Science
Recommender Systems
100%
Fast Convergence
100%
Industrial Application
33%
Dependent Factor
33%
Continuous Time Case
33%
Discrete Time Case
33%