A random walks perspective on maximizing satisfaction of personalized nutrition planning

With the number of people considered to be obese and having chronic disease rising across the world, the role of IT solution in nutrition management and planning has been receiving increased attention by medical professionals in recent years. A key factor toward a successful personalized nutrition planning is an individual's food preference instead of dogmatic nutrition pattern since it is unlikely that an individual would accept the meal plan merely based on the nutrition supplements. However, personal preferences about foods are obviously relatively harder to acquire comparing to common nutrition requirements that can be easily obtained from guidelines. In this paper, we proposed a personalized nutrition planning method based on random walks theory to maximize the planning satisfaction. The personal guidelines generated by the proposed method are expected to potentially improve the healthy diet compliance and thus reduce the risk of chronic diseases of individuals.