In this paper, we propose a decision tree-based machine learning model that leads to food exchange table renewal by classifying food groups through machine learning for existing food and food data found by web crawling. The food exchange table is the standard for food exchange intake when composing a diet such as diet and diet, as well as patients who need nutritional management. The food exchange table, which is the standard for the composition of the diet, takes a lot of manpower and time in the process of revision through the National Health and Nutrition Survey, making it difficult to quickly reflect food changes according to new foods or trends. Since the proposed technique classifies newly added foods based on the existing food group, it is possible to organize a rapid food exchange table reflecting the trend of food. As a result of classifying food into the proposed model in the study, the accuracy of the food group in the food exchange table was 97.45%, so this food classification model is expected to be highly utilized for the composition of a diet that suits your taste in hospitals and nursing homes.
@article{ART002908025}, author={Ji Yun Kim and Jongwan Kim}, title={Classification Model of Food Groups in Food Exchange Table Using Decision Tree-based Machine Learning}, journal={Journal of The Korea Society of Computer and Information}, issn={1598-849X}, year={2022}, volume={27}, number={12}, pages={51-58}, doi={10.9708/jksci.2022.27.12.051}
TY - JOUR AU - Ji Yun Kim AU - Jongwan Kim TI - Classification Model of Food Groups in Food Exchange Table Using Decision Tree-based Machine Learning JO - Journal of The Korea Society of Computer and Information PY - 2022 VL - 27 IS - 12 PB - The Korean Society Of Computer And Information SP - 51 EP - 58 SN - 1598-849X AB - In this paper, we propose a decision tree-based machine learning model that leads to food exchange table renewal by classifying food groups through machine learning for existing food and food data found by web crawling. The food exchange table is the standard for food exchange intake when composing a diet such as diet and diet, as well as patients who need nutritional management. The food exchange table, which is the standard for the composition of the diet, takes a lot of manpower and time in the process of revision through the National Health and Nutrition Survey, making it difficult to quickly reflect food changes according to new foods or trends. Since the proposed technique classifies newly added foods based on the existing food group, it is possible to organize a rapid food exchange table reflecting the trend of food. As a result of classifying food into the proposed model in the study, the accuracy of the food group in the food exchange table was 97.45%, so this food classification model is expected to be highly utilized for the composition of a diet that suits your taste in hospitals and nursing homes. KW - Artificial Intelligence;Machine Learning;Decision Tree;Food Exchange Table;Random Search DO - 10.9708/jksci.2022.27.12.051 ER -
Ji Yun Kim and Jongwan Kim. (2022). Classification Model of Food Groups in Food Exchange Table Using Decision Tree-based Machine Learning. Journal of The Korea Society of Computer and Information, 27(12), 51-58.
Ji Yun Kim and Jongwan Kim. 2022, "Classification Model of Food Groups in Food Exchange Table Using Decision Tree-based Machine Learning", Journal of The Korea Society of Computer and Information, vol.27, no.12 pp.51-58. Available from: doi:10.9708/jksci.2022.27.12.051
Ji Yun Kim, Jongwan Kim "Classification Model of Food Groups in Food Exchange Table Using Decision Tree-based Machine Learning" Journal of The Korea Society of Computer and Information 27.12 pp.51-58 (2022) : 51.
Ji Yun Kim, Jongwan Kim. Classification Model of Food Groups in Food Exchange Table Using Decision Tree-based Machine Learning. 2022; 27(12), 51-58. Available from: doi:10.9708/jksci.2022.27.12.051
Ji Yun Kim and Jongwan Kim. "Classification Model of Food Groups in Food Exchange Table Using Decision Tree-based Machine Learning" Journal of The Korea Society of Computer and Information 27, no.12 (2022) : 51-58.doi: 10.9708/jksci.2022.27.12.051
Ji Yun Kim; Jongwan Kim. Classification Model of Food Groups in Food Exchange Table Using Decision Tree-based Machine Learning. Journal of The Korea Society of Computer and Information, 27(12), 51-58. doi: 10.9708/jksci.2022.27.12.051
Ji Yun Kim; Jongwan Kim. Classification Model of Food Groups in Food Exchange Table Using Decision Tree-based Machine Learning. Journal of The Korea Society of Computer and Information. 2022; 27(12) 51-58. doi: 10.9708/jksci.2022.27.12.051
Ji Yun Kim, Jongwan Kim. Classification Model of Food Groups in Food Exchange Table Using Decision Tree-based Machine Learning. 2022; 27(12), 51-58. Available from: doi:10.9708/jksci.2022.27.12.051
Ji Yun Kim and Jongwan Kim. "Classification Model of Food Groups in Food Exchange Table Using Decision Tree-based Machine Learning" Journal of The Korea Society of Computer and Information 27, no.12 (2022) : 51-58.doi: 10.9708/jksci.2022.27.12.051