System Design of an Intelligent Nutrition Consultation and Recommendation Model

Information and communication technologies have been used to provide valuable services in our daily lives in the form of consultation and recommendation. However, the key factor of a successful service model is the integration of domain knowledge. To show a feasible fusion model as an example, we propose the system design of an intelligent consultation and recommendation framework to assist nutritionists in the environment of cloud computing. We employ the data mining technology of predicting and finding suitable patterns to help nutritionists develop personalized, comprehensive nutrition programs for customers. Decision tree analysis is used to find the matching pairs between customers´ physiological states and their proper diet programs. This system can not only help nutritionists provide better services, but also assist customers to track physiological data, meals, and exercise information. The result demonstrates that our design can serve as a model of intelligent systems for both service providers and consumers.