In this article, we provide a comprehensive introduction to knowledge graphs, which have
recently garnered significant attention from both industry and academia in scenarios that …

Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

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 …

Smart speakers such as Alexa and Google Home introduced Artificial Intelligence (AI) in
millions soon billions of households, making AI an everyday experience. We can now look …

We present the framework of ontology-based data access, a semantic paradigm for
providing a convenient and user-friendly access to data repositories, which has been …

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

This paper presents a dynamic geospatial knowledge graph as part of The World Avatar
project, with an underlying ontology based on CityGML 2.0 for three-dimensional …

The “RNA world” represents a novel frontier for the study of fundamental biological
processes and human diseases and is paving the way for the development of new drugs …

The success of Graph Neural Networks (GNNs) in practice has motivated extensive research
on their theoretical properties. This includes recent results that characterise node classifiers …

Recent advances in natural language understanding and processing have resulted in
renewed interest in natural language interfaces to data, which provide an easy mechanism …