Time series anomaly detection is important for a wide range of research fields and
applications, including financial markets, economics, earth sciences, manufacturing, and …

Ensemble-based methods are among the most widely used techniques for data stream
classification. Their popularity is attributable to their good performance in comparison to …

A model is an artefact to represent a specific concept. It maps properties of the concept into
some abstract representation, driven by the purpose of the model. As such, models …

Abstract The Zwicky Transient Facility (ZTF), a public–private enterprise, is a new time-
domain survey employing a dedicated camera on the Palomar 48-inch Schmidt telescope …

This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

A hands-on approach to tasks and techniques in data stream mining and real-time analytics,
with examples in MOA, a popular freely available open-source software framework. Today …

Smart grids are electric networks that employ advanced monitoring, control, and
communication technologies to deliver reliable and secure energy supply, enhance …

In recent years, data science emerged as a new and important discipline. It can be viewed
as an amalgamation of classical disciplines like statistics, data mining, databases, and …

Big data has become an important issue for a large number of research areas such as data
mining, machine learning, computational intelligence, information fusion, the semantic Web …

This paper provides an overview of recent developments in big data in the context of
biomedical and health informatics. It outlines the key characteristics of big data and how …