The rating matrix is used as input, the inner product of the low-rank matrix of users and items is used to represent the rating, and the objective function is minimized by the alternate least squares (ALS) technique
An additional sharing layer on top of the two neural networks connects the two parallel networks so that the learned user and project potential factors can interactively predict ratings. This model proves that the sparsity problem can be effectively alleviated by using comment text