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 …

Automatic knowledge graph construction aims at manufacturing structured human
knowledge. To this end, much effort has historically been spent extracting informative fact …

One of the most critical tasks for improving data quality and increasing the reliability of data
analytics is Entity Resolution (ER), which aims to identify different descriptions that refer to …

The task of entity alignment between knowledge graphs aims to find entities in two
knowledge graphs that represent the same real-world entity. Recently, embedding-based …

Smart cities have emerged as a result of smart interconnections of people, processes, data,
and things, representing an excellent case study of the Internet of Everything (IoE) paradigm …

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 …

An enormous amount of digital information is expressed as natural-language (NL) text that is
not easily processable by computers. Knowledge Graphs (KG) offer a widely used format for …

Entity Resolution (ER), a core task of Data Integration, detects different entity profiles that
correspond to the same real-world object. Due to its inherently quadratic complexity, a series …

An ontology typically provides a vocabulary describing a domain of interest and a
specification of the meaning of terms in that vocabulary. Depending on the precision of this …

Entity alignment (EA) finds equivalent entities that are located in different knowledge graphs
(KGs), which is an essential step to enhance the quality of KGs, and hence of significance to …