Robust weighted SVD-type latent factor models for rating prediction

Recommending system is a popular tool in many commercial or social platforms which finds interesting products for users based on their preference history. Predicting the ratings of items, such as movies, plays an essential role in the recommending system. In this context, we develop a new type of latent factor models by attaching weights to the entries of the incomplete ratings matrix. The weights are computed after estimating the user/item mean...