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 …

The interest in explainable artificial intelligence has grown strongly in recent years because
of the need to convey safety and trust in the 'how'and 'why'of automated decision-making to …

Abstract Explainability in Artificial Intelligence has been revived as a topic of active research
by the need to demonstrate safety to users and gain their trust in the 'how'and 'why'of …

Modeling how information propagates in social networks driven by peer influence, is a
fundamental research question towards understanding the structure and dynamics of these …

Mining ubiquitous sensing data is important but also challenging, due to many factors, such
as heterogeneous large-scale data that is often at various levels of abstraction. This also …

This paper presents an open cloud based platform for composition, execution, and sharing
of interactive data mining workflows. It is based on the principles of service-oriented …

We present Dedalo, a framework which is able to exploit Linked Data to generate
explanations for clusters. In general, any result of a Knowledge Discovery process, including …

The integration of the two fast-developing scientific research areas Semantic Web and Web
Mining is known as Semantic Web Mining. The huge increase in the amount of Semantic …

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

This paper addresses semantic data mining, a new data mining paradigm in which
ontologies are exploited in the process of data mining and knowledge discovery. This …