Outlier detection in high-dimensional datasets poses new challenges that have not been investigated in the literature. In this paper, we present an integrated methodology for the identification of outliers which is suitable for datasets with higher number of variables than observations. Our...

In this study, we introduce a novel entity matching (EM) framework. It com-bines state-of-the-art EM approaches based on Artificial Neural Networks (ANN) with a new similarity encoding derived from matching techniques that are preva-lent in finance and economics. Our framework is on-par or...

The valuation of house prices is drawing noteworthy attention due to worldwide financial and real estate crises in the last decade. Therefore, there is an immediate need to design more effective predictive systems of house prices. Indeed, investors, creditors, and governments are all interested...

It is almost a truism to argue that data holds a great promise of transformative resources for social good, by helping to address a complex range of societal issues, ranging from saving lives in the aftermath of a natural disaster to predicting teen suicides. Yet it is not public authorities who...

In its Communication "Building a European data economy" the EU Commission discusses the introduction of a new exclusive property right on data ("data producer right") for non-personal (or anonymised) machine-generated data, and mandatory access rights to privately held data for achieving more...