Keyphrases
Recommender Systems
100%
Non-negative Latent Factor Model
100%
Large Sparse Matrices
100%
Alternating Direction Method
100%
Non-negative Latent Factor
66%
Non-negative Matrix Factorization
66%
Collaborative Recommender Systems
66%
High Efficiency
33%
Main Idea
33%
Computational Complexity
33%
Convergence Rate
33%
Computational Cost
33%
Industrial Use
33%
Prediction Accuracy
33%
Learning Systems
33%
Easy-to-implement
33%
Real Application
33%
Big Data
33%
Collaborative Filtering
33%
Memory Complexity
33%
Fast Convergence
33%
Filtering Problems
33%
Non-negativity Constraint
33%
Sparse Matrices
33%
Slow Convergence
33%
Single Feature
33%
Storage Cost
33%
High Convergence
33%
Extremely Sparse
33%
Computer Science
Collaborative Filtering
100%
Recommender Systems
100%
Convergence Rate
66%
nonnegative matrix factorization
66%
Learning Systems
33%
Big Data
33%
Real Application
33%
Fast Convergence
33%
Prediction Accuracy
33%
Real Data Sets
33%
Slow Convergence
33%
Single Feature
33%
Representativeness
33%
Mathematics
Matrix (Mathematics)
100%
Sparse Matrix
100%
Latent Factor
100%
Convergence Rate
50%
Factorization
50%
Real Data
25%
Filtering Problem
25%
Nonnegativity
25%
Representativeness
25%
Engineering
Latent Factor
100%
Filtration
75%
Convergence Rate
50%
Matrix Factorization
50%
Main Idea
25%
Computational Cost
25%
Big Data
25%
Real Application
25%
Real Data
25%
Nonnegativity
25%
Learning Systems
25%
Single Feature
25%
Storage Cost
25%