Efficient extraction of non-negative latent factors from high-dimensional and sparse matrices in industrial applications

Keyphrases

• Industrial Application 100%
• Sparse Matrices 100%
• High-dimensional Matrices 100%
• Non-negative Latent Factor 100%
• Efficient Extraction 100%
• Training Process 40%
• Non-negative Matrix Factorization 40%
• Big Data 20%
• Highly Effective 20%
• Decision Variables 20%
• Single Element 20%
• Sigmoid Function 20%
• Highly Flexible 20%
• Solution Accuracy 20%
• Factorization Method 20%
• General Learning 20%
• Learning Scheme 20%
• Recommender Systems 20%
• Output Factor 20%
• Non-negativity Constraint 20%
• Non-negative Latent Factor Model 20%
• Matrix Factorization Model 20%
• Useful Patterns 20%
• Factor Variables 20%
• Nonnegative Data 20%
• Training Scheme 20%

Computer Science

• Industrial Applications 100%
• Training Process 66%
• Recommender Systems 33%
• Extensibility 33%
• Negativity Constraint 33%
• Matrix Factorization Model 33%
• Big Data 33%
• nonnegative matrix factorization 33%
• Learning Scheme 33%
• Decision Variable 33%
• Experimental Result 33%
• Representativeness 33%
• Matrix Factorization 33%
• Sigmoid Activation Function 33%