Complex Network Based Visual Analytics And Its Application

Complex Network is so complicated that if we only use data table or text to express it, the network will be hard to understand and the contained information could not be revealed. The best way to express complex network is visualization whose related research areas involve complex system, graph theory, statistics, data mining, information visualization and Computer Human Interaction.Current research activities in computer science and physics aim at understanding large and complex networks like the physical Internet, the World Wide Web, the co-author newtork or peer-to-peer systems. The design of adequate visualization methods for such netowrks is an important step towards this aim. As these networks are large or even huge on one hand, and evolving on the other hand, customized visualizations concentrating on their intrinsic structural characteristics are required. The (implicit) relevance of nodes is the most commonly investigated feature. It is usually expressed by a nested decomposition of the node set.This paper discusses the visual analytics and its application based on complex network. Firstly, based on the survey of complex network visualization we summarize and present some of its key technologies, and also probe into some implementation details. Secondly we focus on the application of visual analytics. The aim of this research is showing that the visual analytics based on complex network can be considered as an efficient tool for investigating the structural properties of complex networks. It can be considered as a simulation tool or a compression method and also could provide a friendly interactive visualization user interface.