Chapter 12 - Personalized Expert Recommendation Systems for Optimized Nutrition

Abstract

Personalized dietary advice is increasing in importance due to the expectation of better health with the advancement of nutrigenetics and genetic tests services. However, from the application perspective, the recommendation system is far from mature enough to provide personalized food suggestions to consumers for daily use. The main barrier to connecting genetic information to personalized diets is the complexity of data and the scalability of the applied systems. To target this barrier, a personalized expert recommendation system for optimized nutrition is introduced. In this chapter, the correlation between nutrients and genes is covered, prior to denoting the data categorization of food products, modeling with a type of machine learning model called a deep neural network—a recommendation system with a genetic algorithm—and describing the overall operation of the whole framework. The framework aims to categorize products automatically with the ability to scale with unknown new data and then recommend products through filtering with a model based on individual genetic data with associated phenotypic information. A case study with databases from three different sources is carried out to confirm the system.