Data Collection Framework on Menus satisfying both Preferences and Nutritional Balance

TAAI2021ohata

information

論文タイトル:
Data Collection Framework on Menus satisfying both Preferences and Nutritional Balance

著者:
Yoko Nishihara, Takumi Ohata, and Ryosuke Yamanishi

概要:
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.

発表種別:
国際会議論文

書誌情報:
the 26th International Conference on Technologies and Applications of Artificial Intelligence (TAAI2021)

発表日:
2021年11月18日