Force-directed algorithms have been developed over the last 50 years and used in many
application fields, including information visualisation, biological network visualisation …

Physical interaction in peer learning has been proven to improve students' learning
processes, which is pertinent in facilitating a fulfilling learning experience in learning theory …

Graph sampling frequently compresses a large graph into a limited screen space. This
paper proposes a hierarchical structure model that partitions scale-free graphs into three …

In the advent of big data era, interactive visualization of large data sets consisting of M* 10^
5+ high-dimensional feature vectors of length N (N~ 10^ 3+), is an indispensable tool for …

Interactive visual exploration of large and multidimensional data still needs more efficient
ND → 2D data embedding (DE) algorithms. We claim that the visualization of very high …

There are many tools for the analysis of social networks such as the algorithms for
community detection. However, visualization of these networks enables not only to …

The k-nearest neighbor (k-NN) search is the rudimentary procedure widely used in machine
learning and data embedding techniques. Herein we present a new multi-GPU/CUDA …

We present a new framework for analysis and visualization of complex networks based on
structural information retrieved from their distance k‐graphs and B‐matrices. The …

Because of their overall versatility, complex networks remain the most widely adopted
approach to structure representation—and the recent breakthroughs in graph-based pattern …

Data embedding (DE) and graph visualization (GV) methods are very compatible tools used
in Exploratory Data Analysis for visualization of complex data such as high-dimensional data …