[D] How often do matrix factorization with new data?

I am reviewing how recommendation systems get built and one approach for collaborative recommendations is to have a N x M (user x movie) matrix, where each element represents if the i\_th user liked j\_th movie. To reduce the sparsity of this and to identity 'features', it is recommended to perform matrix factorization to get (N x m) and (m x M) matrices, where m are a # of latent features.

If a new user is added or a new …

data factorization machinelearning