The aim of this critical review paper is threefold:(a) to provide an insight on the impact of
ontology engineering methodologies (OEMs) to the evolution of living and reused …

The deployment of various networks (eg, Internet of Things [IoT] and mobile networks),
databases (eg, nutrition tables and food compositional databases), and social media (eg …

Semantic embedding of knowledge graphs has been widely studied and used for prediction
and statistical analysis tasks across various domains such as Natural Language Processing …

The proliferation of recipes and other food information on the Web presents an opportunity
for discovering and organizing diet-related knowledge into a knowledge graph. Currently …

Artificial Intelligence algorithms are powerful in performing accurate predictions, but they are
often considered black boxes as they do not provide any explanation about how outputs are …

Automating ontology construction and curation is an important but challenging task in
knowledge engineering and artificial intelligence. Prediction by machine learning …

Ontology alignment plays a critical role in knowledge integration and has been widely
investigated in the past decades. State of the art systems, however, still have considerable …

AI-based software applications for personalized nutrition have recently gained increasing
attention to help users follow a healthy lifestyle. In this paper, we present a knowledge …

Explainable AI aims at building intelligent systems that are able to provide a clear, and
human understandable, justification of their decisions. This holds for both rule-based and …

We propose a knowledge model for capturing dietary preferences and personal context to
provide personalized dietary recommendations. We develop a knowledge model called the …