International Business Machines Corporation
PROVIDING RECOMMENDATIONS VIA MATRIX FACTORIZATION

Abstract:

At least one original data matrix is received, wherein the at least one original data matrix includes information of at least one user. At least one submatrix is sampled from the at least one original data matrix, wherein the at least one submatrix includes at least part of information of the at least one user. At least one matrix approximation sub-model is generated for the at least one submatrix based on a trained matrix approximation model, wherein the matrix approximation sub-model captures some preferences of the at least one user.