Optimization of Movie Recommender Systems using Differential Evolutionary Bees Algorithm for Clusterings

One of the most significant issues in recommender systems is finding the optimal number of clusters and convergence speed. A combinatorial Bees Algorithm (BA) and Differential Evolution (DE) are proposed to cope with this problem. In this research, we perform a comparative study on the efficiency of DE for a movie recommender system and the best hyperparameter settings on the MovieLens dataset.