Ontology learning is the process of acquiring (constructing or integrating) an ontology (semi-
) automatically. Being a knowledge acquisition task, it is a complex activity, which becomes …

Background: Cyber defense is reactive and slow. On average, the time-to-remedy is
hundreds of times larger than the time-to-compromise. In response, Human Digital Twins …

A large number of information systems use many different individual schemas to represent
data. Semantically linking these schemas is a necessary precondition to establish …

Ontologies play a key role in the advent of the Semantic Web. An important problem when
dealing with ontologies is the modification of an existing ontology in response to a certain …

Ontology evolution aims at maintaining an ontology up to date with respect to changes in the
domain that it models or novel requirements of information systems that it enables. The …

The research area of ontology engineering seems to have reached a certain level of
maturity, considering the vast amount of contemporary methods and tools for formalising and …

One of the major problems of large scale, distributed and evolving ontologies is the potential
introduction of inconsistencies. In this paper we survey four different approaches to handling …

Ontology learning techniques serve the purpose of supporting an ontology engineer in the
task of creating and maintaining an ontology. In this chapter, we present a comprehensive …

Ontology learning aims at generating domain ontologies from various kinds of resources by
applying natural language processing and machine learning techniques. It is inherent to the …

We study the problem of evolution for Knowledge Bases (KBs) expressed in Description
Logics (DLs) of the DL− Lite family. DL− Lite is at the basis of OWL 2 QL, one of the tractable …