# Ontology-Based Nutritional Recommender System
## 2 State-of-The-Art
### Health and Nutrition Ontologies  
In health care, an ontology is a formal conceptualization of a health-related domain [24]. Ontologies are used to model the medical domain's semantics, making its terminology explicit [25; 26]. Currently, a great variety of ontologies has been developed covering several domains that go from representing the human disease domain to creating medical terminology, enabling medical information systems to be interoperable and facilitating knowledge interchange across multiple disciplines [27; 28]. Concretely, in the health domain, there is a variety of interesting works proposed by [PERSON] et al. [29]. They defined the Alzheimer Disease Ontology (ADO) to cover the absence of formal representation in this disease. The ontology was built using various knowledge resources such as the National Center for Biomedical Ontology to extract synonyms and abstracts obtained from PubMed to construct a dictionary or encyclopedia and atlas of the mentioned disease. Following the same domain, [PERSON] et al. [30] built the coronavirus Infectious Disease Ontology (CIDO) to cover areas related to coronavirus diseases such as etiology, transmission, prevention, and treatment, among others. The CIDO integrates more than 300 ontologies and contains 4000 terms imported from some 20 other ontologies such as ChEBI [31] or the Human Phenotype Ontology [32]. It defines axioms that relate, for instance, the virus SARS-CoV-2 to the produced disease COVID-19 or the phenotype that manifests the disease in infected patients.  
Focusing on the nutritional domain, [PERSON] et al. [33] proposed the Diabetes Mellitus Treatment Ontology (DMTO) as a knowledge base that provides a detailed description of a patient's conditions, profiles, complications, and symptoms of Type 2 Diabetes Mellitus (T2 DB) treatment. In the same line, [PERSON] et al. [34] emphasized the application of the Semantic Web in nutrition research. They proposed the Ontology for Nutritional Epidemiology (ONE), a formal way to specifically relate terms used in this domain. To build the ontology, the authors analyzed multiple articles and ontologies related to the nutritional epidemiology domain. More related to the food recommendation, [PERSON] et al. [35] described the process of building FoodKG, a food knowledge graph that links recipes to their ingredients and ingredients to their nutritional data. Following the same line, [PERSON] [36] presented the Ontology-Driven Mobile Safe Food Consumption System (FoodWiki) and the Food Ontology Knowledge Base (FOKB). The system provides a web service that enables food-sensitive users obtain detailed information about their consumed nutrients individually. It does not consider recipes, only individual ingredients. The retrieved data are based on the FOKB, which semantically describes health risk groups, unsuitable components for those groups, and unhealthy ingredients with side effects taking into account users' health status.  
In this work, we implemented an ontology to define diets recommended to users, considering their health status. _Diets_ are related to a set of recipes, and each recipe is semantically described in terms of ingredients. Taking into account that the FOKB defines a detailed specification of ingredients, part of that model has been reused to build our ontology. An in-depth description of the ontology conceived of in this work can be found in Section 3.1.