Abstract Data Mining and Knowledge Discovery in Databases (KDD) is a research field
concerned with deriving higher-level insights from data. The tasks performed in that field are …

Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …

With the proliferation of heterogeneous health care data in the last three decades,
biomedical ontologies and controlled biomedical terminologies play a more and more …

Actionable Cognitive Twins are the next generation Digital Twins enhanced with cognitive
capabilities through a knowledge graph and artificial intelligence models that provide …

The paper proposes a novel architecture for explainable artificial intelligence based on
semantic technologies and artificial intelligence. We tailor the architecture for the domain of …

Abstract The Data Mining OPtimization Ontology (DMOP) has been developed to support
informed decision-making at various choice points of the data mining process. The ontology …

Within maintenance management activities, engineers need to select maintenance
strategies so to carry out the technical maintenance actions. A single equipment is …

The ML-Schema, proposed by the W3C Machine Learning Schema Community Group, is a
top-level ontology that provides a set of classes, properties, and restrictions for representing …

The selection of metafeatures for metalearning (MtL) is often an ad hoc process. The lack of
a proper motivation for the choice of a metafeature rather than others is questionable and …

Ontology has historically emerged from the meaning of this term against research
methodology in order to the knowledge and technology developments. A term that has been …