As our dependence on intelligent machines continues to grow, so does the demand for more
transparent and interpretable models. In addition, the ability to explain the model generally …

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 …

As a powerful expression of human knowledge in a structural form, knowledge graph (KG)
has drawn great attention from both the academia and the industry and a large number of …

More and more weakly structured, and irregular data sources are becoming available every
day. The schema of these sources is useful for a number of tasks, such as query answering …

A major research challenge is to perform scalable analysis of large-scale knowledge graphs
to facilitate applications like link prediction, knowledge base completion and reasoning …

The ever increasing prevalence of publicly available structured data on the World Wide Web
enables new applications in a variety of domains. In this paper, we provide a conceptual …

With Knowledge Graphs (KGs) at the center of numerous applications such as recommender
systems and question-answering, the need for generalized pipelines to construct and …

The rapid generation of large amounts of information about the coronavirus SARS-CoV-2
and the disease COVID-19 makes it increasingly difficult to gain a comprehensive overview …

Learning description logic (DL) concepts from positive and negative examples given in the
form of labeled data items in a KB has received significant attention in the literature. We …

Abstract Concept Induction refers to the problem of creating complex Description Logic class
descriptions (ie, TBox axioms) from instance examples (ie, ABox data). In this paper we look …