The analysis of large graphs plays a prominent role in various fields of research and is
relevant in many important application areas. Effective visual analysis of graphs requires …

Multilevel optimization aims at reducing the cost of executing a target network-based
algorithm by exploiting coarsened, ie, reduced or simplified, versions of the network. There …

The overview-driven visual analysis of large-scale dynamic graphs poses a major
challenge. We propose Multiscale Snapshots, a visual analytics approach to analyze …

Diagnosing a large-scale sensor network is a crucial but challenging task. Particular
challenges include the resource and bandwidth constraints on sensor nodes, the …

The increasing size of Big Data is often heralded but how data are transformed and
represented is also profoundly important to knowledge discovery, and this is exemplified in …

Many real-world datasets are large, multivariate, and relational in nature and relevant
associated decisions frequently require a simultaneous consideration of both attributes and …

The analysis of large graphs plays a prominent role in various fields of research and is
relevant in many important application areas. Effective visual analysis of graphs requires …

Despite their widespread use, network visualisations can be rather challenging to design
and use. This is due to the fact that such visualisations are generally used to represent …

The amount of information flowing across communication networks has rapidly increased.
The highly dynamic and complex networks, represented as large graphs, make the analysis …

We present a visual analytics paradigm and a system prototype for exploring Web-scale
graphs. A web-scale graph is described as a graph with~ one trillion edges and~ 50 billion …