Java Deep Learning Projects

Model-based collaborative filtering

Collaborative filtering methods are classified as memory-based, such as the user-based algorithm and model-based collaborative filtering (kernel mapping is recommended). In the model-based collaborative filtering technique, users and products are described by a small set of factors, also called latent factors (LFs). The LFs are then used to predict the missing entries. The Alternating Least Squares (ALS) algorithm is used to learn these latent factors.

Compared to a memory-based approach, a model-based approach can handle the sparsity of the original matrix better. This is also scalable, faster, and can avoid overfitting issues. However, it is not flexible and adaptable because it is difficult to add data ...