The exploratory visual analysis (EVA) of time series data uses visualization as the main
output medium and input interface for exploring new data. However, for users who lack …

The term 'episode'refers to a time interval in the development of a dynamic process or
behaviour of an entity. Episode‐based data consist of a set of episodes that are described …

The application potential of Visual Analytics (VA), with its supporting interactive 2D and 3D
visualization techniques, in the environmental domain is unparalleled. Such advanced …

In data analysis, recognizing unusual patterns (outliers’ analysis or anomaly detection)
plays a crucial role in identifying critical events. Because of its widespread use in many …

Probabilistic-based non-linear dimensionality reduction (PB-NL-DR) methods, such as t-
SNE and UMAP, are effective in unfolding complex high-dimensional manifolds, allowing …

Abstract The field of Deep Visual Analytics (DVA) has recently arisen from the idea of
developing Visual Interactive Systems supported by deep learning, in order to provide them …

Cyber-Physical Systems (CPSs) are becoming increasingly complex and interconnected as
they attempt to meet the demands of evolving society. As a result, monitoring and …

Air quality analysis helps analysts understand the state of atmospheric pollution and its
changing trends, providing robust data and theoretical support for developing and …

The advertising revenue of online shopping platforms comes from the users who click on the
advertisements and purchases the advertised goods. Therefore, to accurately advertise and …

Analysis of large, high-dimensional, and heterogeneous datasets is challenging as no one
technique is suitable for visualizing and clustering such data in order to make sense of the …