… a few items out of the whole in a recommender system used by Amazon or Taobao [4], [5].
In … Nonnegative Latent Factor model. NeuMF Neural Matrix Factorization model [75]. DCCR …

… Wang, “A fast non-negative latent factor model based on generalized momentum method,” …
nonnegative latent factor model for large-scale sparse matrices in recommender systems via …

… to perform unconstrained non-negative latent factor analysis (UNLFA) on HiDS matrices.
To … Zhou, “Randomized latent factor model for high-dimensional and sparse matrices from …

… Note that unlike a traditional sparse matrix whose entries are mostly zeroes, an HiDS … , “A
nonnegative latent factor model for large-scale sparse matrices in recommender systems via …

… Thus, NMF is widely used in CF recommender systems’ … the user and item latent factor
matrices by explicit information, … efficient dense and sparse matrix multiplication kernels in CUDA…

… Li, “Efficient extraction of non-negative latent factors from high-dimensional and sparse
matrices … Zhu, “A nonegative latent factor model for large-scale sparse matrices in recommender …

… High-dimensional and sparse matrices (HiDS) matrices with non-negativity constraints are …
sparse non-negative matrix factorization model for largescale recommender systems on GPUs…

… In many industrial applications related to big data, a so-called high-dimensional sparse matrix
is often used to represent relationships between entities, where the sparsity mainly results …

… of the proposed SNbased model in building CF-based recommender systems, its accuracy
… A Nonnegative latent factor model for large-Scale sparse matrices in recommender systems …

… (DVMF) is proposed for large scale sparse dataset. DVMF is based on latent factors to …
its state-of-the-art performance in recommender systems. It has been proved the ability to use …