The Exploration of Restaurant Recommender System

Journal of computer sciences

article

Tora Fahrudin¹  Nelsi Wisna¹ 

[1]School of Applied Sciences, Telkom University

关键词: Restaurant;    Recommender System;    Rating;    Collaborative Filtering;   

DOI  :  10.3844/jcssp.2022.784.791

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

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.

【 授权许可】

CC BY