AI Food Recommendation Systems
Sin-Hua Wu, Jung Hsiao, Yansheng Wu, Jin-Tsong Jeng · 2022 IET International Conference on Engineering Technologies and Applications (IET-ICETA) · 2022
In an information-rich generation, recommendation systems is very important. Hence, in this paper we use the Google Map API and the feedback record of user to build data set on database for the AI (Artificial Intelligence) food recommendation systems. In order to make a recommendation system that knows more than the user, we combine the indispensable food and drink according to the preferences of users to recommend the favorite of users. That is, the AI food recommendation system uses GAE (Graph Autoencoder) and regional filtering to predict the favorite of users. Besides, the AI food recommendation system is proposed to use GAE and regional filtering to predict the user's favorite degree by means of deep learning, and then push it to the user through the Line Bot that can recommend the store to the favorite food of users on nearby, and then feedback to our system after the user uses it, which makes the proposed system more complete and accurate.