The use and creation of machine‐learning‐based solutions to solve problems or reduce
their computational costs are becoming increasingly widespread in many domains. Deep …

Visual data analysis can be envisioned as a collaboration of the user and the computational
system with the aim of completing a given task. Pursuing an effective system‐user …

Deep neural networks are now rivaling human accuracy in several pattern recognition
problems. Compared to traditional classifiers, where features are handcrafted, neural …

There is fast‐growing literature on provenance‐related research, covering aspects such as
its theoretical framework, use cases, and techniques for capturing, visualizing, and …

Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the
learning analytics community. The Society of Learning Analytics Research is home to the …

Visual analytics systems integrate interactive visualizations and machine learning to enable
expert users to solve complex analysis tasks. Applications combine techniques from various …

Significant progress to integrate and analyse multimodal data has been carried out in the
last years. Yet, little research has tackled the challenge of visualising and supporting the …

We describe visual analytics solutions aiming to support public health professionals, and
thus, preventive measures. Prevention aims at advocating behaviour and policy changes …

In this paper, we list the goals for and the pros and cons of guidance, and we discuss the
role that it can play not only in key low-level visualization tasks but also the more …

Multimodal Learning Analytics (MMLA) innovations make use of rapidly evolving sensing
and artificial intelligence algorithms to collect rich data about learning activities that unfold in …