The Matrix-Factorization (MF) based models have become popular when building Collaborative Filtering (CF) recommender systems, due to the high accuracy and scalability. Most of nowadays matrix factorization models don't have acceptable execution time during to large datasets. In this article, we introduce a new collaborative filtering recommender system, based on matrix factorization by using genetic algorithm.
