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- W4294384191 abstract "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 of these attribute ratings using theCollaborative Filtering (CF) technique. Experiments were performed with k-NN,SVD, Slope One, and Co-Clustering algorithms, while RMSE, MSE, MAE, and FCPwere used as evaluation metrics. The results showed that the service restaurantrating predictions produced the best average MSE and RMSE accuracy in 5 and10-fold cross-validation. Furthermore, the best hyperparameter of algorithmsusing Grid Search was achieved in restaurant rating prediction. In conclusion,SVD surpasses other algorithms in MSE and RMSE for all scenarios." @default.
- W4294384191 created "2022-09-03" @default.
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- W4294384191 date "2022-08-01" @default.
- W4294384191 modified "2023-09-30" @default.
- W4294384191 title "The Exploration of Restaurant Recommender System" @default.
- W4294384191 doi "https://doi.org/10.3844/jcssp.2022.784.791" @default.
- W4294384191 hasPublicationYear "2022" @default.
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