Matrix Factorization using Embedding Layers

Matrix factorization plays a major role in the recommender systems. It:

• decreases the computations
• improves the performance as it increases the robustness of the system w.r.t. the noise.

The process of the matrix factorization using embedding layers is shown in the following figure:

Codes & Results

The code consist of two parts. One is for the data preprocessing, and one implements and matrix factorization using embedding layer, and gets the results.

To see the Github repository for this project, see Github.

References

1. Recommender Systems Handbook; Ricci, Rokach, Shapira
2. Statistical Methods for Recommender Systems; Agarwal, Chen