Abstract

Semantic technologies, such as knowledge graphs, ontologies and reasoning have been developed as a bridge between human and machine conceptualizations of a domain of interest.

They may provide human-centric and semantic interpretation and be used to produce semantic explanations, i.e. explanations based on semantic concepts coming from knowledge graphs and ontologies.

I will show several ideas and proposals on how knowledge graphs, ontologies and schemas, both from arbitrary domain and from the domain of machine learning in particular, may be combined with machine learning for: i) providing semantic explanations, ii) facilitating generation of other types of explanations (textual or visual explanations).