Yoko Nishihara, Takumi Ohata, Ryosuke Yamanishi: Data Collection Framework on Menus satisfying both Preferences and Nutritional Balance, Proc. of the 26th International Conference on Technologies and Applications of Artificial Intelligence, pp.323-328, 2021.

Having meals with nutritional balanced is an excellent choice to live in healthy and long. However, people may avoid meals with nutritional balanced if they are not matched with their preferences even though they know well the importance of nutritional balance. Meals that satisfy both preferences and nutritional balance should be recommended. This paper proposes a data collection framework on menus satisfying both preferences and nutritional balance. The proposed framework asks a user to think up a menu that consists of several meals while considering both preferences and nutritional balance. The menu is evaluated in its nutritional balance and given a score. The score is relatively compared with the previous scores, and a face mark which is the feedback to the user is decided. If a score is improved even if slightly, a smiley face mark is shown. In contrast, if a score is worsened significantly, a crying face mark is shown. In other cases, a normal face mark is shown to the user. The user can learn characteristics of the menus with nutritional balanced by referring to the feedback. The framework collects data on menus that satisfy both preferences and nutritional balance. The authors conducted evaluation experiments. Experimental results showed that the proposed framework could collect data on menus satisfying both preferences and nutritional balance without tough labor.