The Exploration of Restaurant Recommender System

The exploitation of Recommender Systems (RS) isstill a challenge, hence it is important to explore the three correlatedattributes, such as restaurant, food, and service ratings. Therefore, thisstudy provides an in-depth review these attribute ratings using theCollaborative Filtering (CF) technique. Experiments were performed with k-NN,SVD, Slope One, Co-Clustering algorithms, while RMSE, MSE, MAE, FCPwere used evaluation metrics. results showed that restaurantrating predictions produced best average MSE RMSE accuracy in 5 and10-fold cross-validation. Furthermore, hyperparameter algorithmsusing Grid Search was achieved restaurant rating prediction. In conclusion,SVD surpasses other algorithms for all scenarios.