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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Constructing a Diet Recommendation System Based on Fuzzy Rules and Knapsack Method
verfasst von : Rung-Ching Chen, Yung-Da Lin, Chia-Ming Tsai, Huiqin Jiang
Erschienen in: Recent Trends in Applied Artificial Intelligence
Verlag: Springer Berlin Heidelberg
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Many people suffer from three chronic diseases(diabetes, hypertension, cholesterol), and they often use search engine to collect related information. However, most of dietary information on the networks is not convenient for users to collect about the diet recommendations. In this paper, a diet recommendation system is suggested which can recommend a rational diet for users. We design a diet recommendation system which has the expert knowledge of three high chronic diseases. We use Protégé to establish ontology and OWL DL to construct the structure of knowledge. The system uses fuzzy logic as a guide prior to inference. According to the patient’s health information, the system infers daily calories requirement, and then use JENA inference device and JENA rule format to build our knowledge of the rules. The Knapsack-like algorithm is used to recommend suitable foods for users. The system was evaluated by nutritionists to prove it is effective.