Ontologies are at the core of the semantic web. As knowledge bases, they are very useful
resources for many artificial intelligence applications. Ontology learning, as a research area …

Semantic annotation is a crucial part of achieving the vision of the Semantic Web and has
long been a research topic among various communities. The most challenging problem in …

In the last decade, ontologies have become widely adopted in a variety of fields ranging
from biomedicine, to finance, engineering, law, and cultural heritage. The ontology …

The quest for acquiring a formal representation of the knowledge of a domain of interest has
attracted researchers with various backgrounds into a diverse field called ontology learning …

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 …

In this chapter we provide an overview on some of the main issues in machine learning. We
discuss machine learning both from a formal and a statistical perspective. We describe some …

Abstract The Web of Data is one of the perspectives of the Semantic Web. In this context,
concept learning services, supported by multirelational machine learning, have been …

Many applications require explainable node classification in knowledge graphs. Towards
this end, a popular “white-box” approach is class expression learning: Given sets of positive …

Abstract Concept induction, which is based on formal logical reasoning over description
logics, has been used in ontology engineering in order to create ontology (TBox) axioms …