Research On Personalized Healthy Diet Recommendation Method

With the improvement of people's living standards,dietary health has become the focus of public concern.A scientific and rational diet is beneficial to physical health,and it has a very important role in the treatment of the disease.Due to the lack of domestic nutritionists,people need to take an effective approach to diet planning.In this situation,dietary recommendations came into being.It can assist users in making scientific dietary decisions.Dietary recommendations need to take into account both interest and nutrition.How to provide users with dietary recommendation services that meet the needs of both nutrition and interest is a practical research topic.This article focuses on personalized healthy diet recommendations based on nutritional balance and personalized dietary needs.The research content is as follows:1.Improved fast non-dominating genetic algorithm.In order to solve the problem of complex process,slow calculation speed and easy to fall into local optimum in the process of multi-objective optimization for dietary nutrition balance,this paper proposes an improved fast non-dominating genetic algorithm.Based on NSGA2,this algorithm introduces a differential mutation operator with guidance to enhance the local search ability of the algorithm.By optimizing the benchmark test function,it shows that the algorithm can avoid falling into a local optimum.For the problem that the search accuracy of the algorithm is not high,a variable scaling factor strategy is proposed,so that the convergence speed and reliability of the algorithm are better taken into account.2.Improved collaborative filtering algorithm.In order to solve the user's dietary interest problem that traditional collaborative filtering algorithm needs to solve,this paper proposes a solution that uses the Slope One algorithm,K-Means clustering algorithm,and similarity algorithm in the collaborative filtering recommendation algorithm.A weighted Slope One algorithm based on K-Means clustering was proposed to implement the recommendation function.3.A personalized healthy diet recommendation method was proposed.The recipe data and ingredients nutrient composition data were obtained through the Scrapy crawler framework.Nutrition catering was optimized based on the improved NSGA2 algorithm,and the user's diet preference was recommended based on the improved collaborative filtering algorithm.And it was applied to the diet recommendation system to achieve the personalized nutritional dish recommendation function.The experimental results show that the personalized health diet recommendation method proposed in this paper can design a catering program that meets the user's preference and nutrition needs.It balances the relationship between personalization and nutritional balance well and achieves the purpose of a healthy diet.