Various graphs such as web or social networks may contain up to trillions of edges.
Compressing such datasets can accelerate graph processing by reducing the amount of I/O …

With the prevalence of big data, there is a growing need for algorithms and techniques for
visualizing very large and complex graphs. In this article, we review layout algorithms and …

Event-based egocentric dynamic networks are an important class of networks widely seen in
many domains. In this paper, we present a visual analytics approach for these networks by …

The visualization of network traffic flows is an open problem that affects the control and
administration of communication networks. Feature vectors used for representing traffic …

Hierarchical abstraction is a scalable strategy to deal with large networks. Existing
visualization methods have allowed to aggregate the network nodes into hierarchies based …

Parallel coordinate is a popular tool for visualizing high-dimensional data and analyzing
multivariate data. With the rapid growth of data size and complexity, data clutter in parallel …

Data visualization is the main focusing concept in big data analysis for processing and
analyzing multi variate data, because of rapid growth of data size and complexity of data …

In this paper we propose an approach to the development of the computer network
visualization system for security monitoring, which uses a conceptually new model of …

Ontologies are formal representations of concepts and complex relationships among them.
They have been widely used to capture comprehensive domain knowledge in areas such as …

A GraphMaps is a system that visualizes a graph using zoom levels, which is similar to a
geographic map visualization. GraphMaps reveals the structural properties of the graph and …