… a novel robust collaborative filtering method based on non-negative matrix factorization and
… -norm as the loss function of non-negative matrix factorization based CF model to develop a …

… They predict user tastes in recommender systems based on collaborative filtering by
presenting a novel approach, factorizing the rating matrix into two nonnegative matrices with …

… This method creates a model by collecting information about users' past activities, analyzing
… , the method based on collaborative filtering is used. The collaborative filtering method is …

… Therefore, in addition to reviewing the basic and regularized NMFs, our attention shifts to
focus on graph regularized non-negative matrix factorization (GNMF), which is widely and …

… adopts single element based non-negative matrix factorization model, and it is very suitable
for recommender system integrating content-based and collaborative filtering, and improve …

… technique to tackle the data sparsity issue of collaborative filtering. In the embedding layer,
a non-negative constraint is imposed to extract the non-negative features of user-items. The …

… In this paper, an improvised hybrid collaborative filtering RS is proposed. The model …
Non-negative Matrix Factorization is used as collaborative filtering technique for rating prediction. …

… Collaborative filtering (CF) has been demonstrated to be an efficient and practical approach
compared to other methods. CF uses users’ feedback to generate recommendations. The …

… -based method (Non-Negative Matrix Factorization-based … in collaborative filtering methods
(Sadeghi and Keyvanpour, 2019a). We use non-negative matrix factorization (NMF) method …

… Zhu, “An efficient nonnegative matrix-factorization-based approach to collaborative filtering
for recommender systems,” IEEE Transactions on Industrial Informatics, vol. 10, no. 2, pp. …