How can personal knowledge graphs contribute to precision nutrition?

Abstract

Nutrition is undoubtedly a significant factor in disease prevention, and keeping track of it is incredibly important for our overall health. One of the latest technologies that has emerged to help healthcare professionals and users make informed decisions is the Knowledge Graph (KG). These models have been used to implement various knowledge-based systems related to nutrition, taking advantage of the vast amount of information about foods, nutrients, dietary recommendations, and healthy eating patterns available in multiple media. However, a KG needs to incorporate individual information, represented by a personal knowledge graph (PKG), to facilitate reasoning and decision-making about an individual's diet or nutrition plan. This article introduces the concept of a Personal Nutritional Knowledge Graph (PNKG), a structured information resource containing data related to an individual's specific nutritional aspects. This study analyzes the concepts and requirements and proposes a generic architecture to assist developers in building adaptive personalized nutrition advice systems