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 …

In many applications of information systems learning algorithms have to act in dynamic
environments where data are collected in the form of transient data streams. Compared to …

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 …

Class imbalance poses new challenges when it comes to classifying data streams. Many
algorithms recently proposed in the literature tackle this problem using a variety of data …

The aim of this study is to provide an overview the state-of-the-art elements of text
classification. For this purpose, we first select and investigate the primary and recent studies …

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 …

Most machine learning models are static, but the world is dynamic, and increasing online
deployment of learned models gives increasing urgency to the development of efficient and …

Abstract Number of connected devices is steadily increasing and these devices continuously
generate data streams. Real-time processing of data streams is arousing interest despite …

The significant growth of interconnected Internet‐of‐Things (IoT) devices, the use of social
networks, along with the evolution of technology in different domains, lead to a rise in the …

This paper presents a comprehensive procedure to predict geological conditions (ie, rock
mass types) for a tunneling boring machine (TBM) based on big operational data including …