Journal of Advanced Computational Intelligence and Intelligent Informatics
Online ISSN : 1883-8014
Print ISSN : 1343-0130
ISSN-L : 1883-8014
Regular Papers
A Chronic Disease Diet Recommendation System Based on Domain Ontology and Decision Tree
Rung-Ching ChenChung-Yi HuangYu-Hsien Ting
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JOURNAL OPEN ACCESS

2017 Volume 21 Issue 3 Pages 474-482

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Abstract

As society develops and science and technology improve, people have come to care more about a healthy diet. Diet types have gradually changed and focused more on health management. Taiwan is becoming an aging society in which individuals have irregular lifestyles, long-term unhealthy diets, stressful work, and chronic diseases such as diabetes, hypertension, and high cholesterol. However, most dietary recommendation systems cannot give dietary recommendations for patients with chronic diseases. Though healthy foods are recommended, the systems contain little information on whether nutrients are in balance. Therefore, this study constructed a diet recommendation system for chronic diseases using expert knowledge, which enables more convenient and precise dietary recommendations for chronic diseases. In this study, we use an ontology, decision trees, and Jena to construct the recommendation system. The dietary recommendations results are evaluated by dietitians, and the verification accuracy is 100%. Therefore, this system of dietary recommendations can provide convenient, healthy, dietary recommendations for nutrients for patients with chronic diseases.

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