  We propose a knowledge model for capturing dietary preferences and personal
context to provide personalized dietary recommendations. We develop a knowledge
model called the Personal Health Ontology, which is grounded in semantic
technologies, and represents a patient's combined medical information, social
determinants of health, and observations of daily living elicited from
interviews with diabetic patients. We then generate a personal health knowledge
graph that captures temporal patterns from synthetic food logs, annotated with
concepts from the Personal Health Ontology. We further discuss how lifestyle
guidelines grounded in semantic technologies can be reasoned with the generated
personal health knowledge graph to provide appropriate dietary recommendations
that satisfy the user's medical and other lifestyle needs.
