Multimodal Analytics in Big Data architectures implies compounded configurations of the
data processing tasks. Each modality in data requires specific analytics that triggers specific …

Abstract Predictive Process Monitoring (PPM) extends classical process mining techniques
by providing predictive models that can be applied at runtime during the execution of a …

The research and technological area of data management encompasses various concepts,
techniques, algorithms and technologies, including data modeling, data integration and …

Structural network analysis retrieves the holistic patterns of interactions among network
instances. Due to the unprecedented growth of data availability, it is time to take advantage …

In business applications, data integration is typically implemented as a data warehouse
architecture. In this architecture, heterogeneous and distributed data sources are accessed …

Machine learning models are routinely integrated into process mining pipelines to carry out
tasks like data transformation, noise reduction, anomaly detection, classification, and …

To gain a comprehensive understanding of a patient's health, advanced analytics must be
applied to the data collected by electronic health record (EHR) systems. However, managing …

Anonymization is an important aspect of data privacy protection, especially in the context of
sensitive personal information collected through sensors. In this paper, we propose a new …

During recent years, we observe a widespread of new data sources, especially all types of
social media and IoT devices, which produce huge data volumes, whose content ranges …

We consider graphs to model uncertain facts as edges, linking involved entities, with weights
reflecting uncertainty degree. Rules are used to create new edges from the existing ones …