Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data.
For DR techniques to be useful in exploratory data analysis, they need to be adapted to …

Visual analytics enables us to analyze huge information spaces in order to support complex
decision making and data exploration. Humans play a central role in generating knowledge …

Knowledge about visualization tasks plays an important role in choosing or building suitable
visual representations to pursue them. Yet, tasks are a multi-faceted concept and it is thus …

Visual analytics (VA) systems help data analysts solve complex problems interactively, by
integrating automated data analysis and mining, such as machine learning (ML) based …

With the surge of data-driven analysis techniques, there is a rising demand for enhancing
the exploration of large high-dimensional data by enabling interactions for the joint analysis …

Dimension reduction algorithms and clustering algorithms are both frequently used
techniques in visual analytics. Both families of algorithms assist analysts in performing …

Visual analytics (VA) research provides helpful solutions for interactive visual data analysis
when exploring large and complex datasets. Due to recent advances in eye tracking …

Las tecnologías utilizadas en los procesos de aprendizaje implican el registro de todas las
actividades realizadas. Estos datos se pueden aprovechar para la evaluación de …

User tasks play a pivotal role in visualization design and evaluation. However, the term
'task'is used ambiguously within the visualization community. In this article, we critically …

Interactive detection of system anomalies is disclosed. One example is a system including a
data processor, an anomaly processor, and an interaction processor. Input data related to a …