In recent years, the availability of time series streaming information has been growing
enormously. Learning from real-time data has been receiving increasingly more attention …

Activity recognition aims to provide accurate and opportune information on people's
activities by leveraging sensory data available in today's sensory rich environments …

We are seeing an enormous increase in the availability of streaming, time-series data.
Largely driven by the rise of connected real-time data sources, this data presents technical …

Classifiers deployed in the real world operate in a dynamic environment, where the data
distribution can change over time. These changes, referred to as concept drift, can cause the …

Data stream mining has become an important research area over the past decade due to the
increasing amount of data available today. Sources from various domains generate a near …

In massive data analysis, data usually come in streams. In the last years, several studies
have investigated novelty detection in these data streams. Different approaches have been …

Abstract Automated Guided Vehicles (AGVs) have become an indispensable component of
Flexible Manufacturing Systems. AGVs are also a huge source of information that can be …

Abstract Motivated by the Statistical Learning Theory (SLT), which provides a theoretical
framework to ensure when supervised learning algorithms generalize input data, this …

Developing effective and efficient data stream classifiers is challenging for the machine
learning community because of the dynamic nature of data streams. As a result, many data …

Self-improving system integration (SISSY) aims at mastering the challenges of system
organisation decisions for subsystems with highly dynamic behaviours. This is achieved by …