The Research And Implementation Of Information Network Visualization Analysis System

Human society and virtual network society have various types of networks, such as communication network, social network, academic cooperation network, biological gene network and so on. Thus, it is necessary to solve the problem of how to analyze networks efficiently.Data visualization can transform the invisible phenomena into visible graphical symbols. And users can get useful knowledge var data visualization. Therefore, more and more researchers use data visualization and analysis help find useful information in networks.Because the network has already affected peoples life, network visualization and analysis becomes a hot problem. Since the networks are always very large and contain tens of thousands or even millions of nodes and links. But drawing such large networks on the limited screen with constrained browser rendering speed is usually impossible and meaningless. Thus, the scale of network is a challenge of network visualization, and sampling is a necessary strategy of network visualization. The various types of nodes and links in the information network makes visual analysis more complex and difficult. In this paper,we propose a sampling method considering both multiple types of nodes and links, supporting sampling the heterogeneous information networks directly and efficiently. Furthermore, we develop a information network visualization tool to help users explore useful information in the network.The main research contents are as follows:l.This paper proposes an eigenvector centrality based sampling method for heterogeneous network. Most of networks in real world are very large and usually have multiple types of entities or relations which can be seen as heterogeneous networks. Thus, sampling is important in network visualization. However, traditional sampling methods are not applicable in such heterogeneous network visualization any more. So we design a sampling algorithm, considering both multiple types of nodes and links, supporting sampling the heterogeneous networks directly and efficiently. Users can deeply explore and dig up useful information through changing the sampled network dynamically.2.This paper designs and implements a information network visualization tool. The exiting network visualization tools mostly show the known network structure. Their process of visual exploration is not friendly and users can not use them explore the information network easily. Thus, it is necessary to develop an information network visualization tool to help users visual analyze the information network. In this paper, we design and implement an information network visualization tool with the proposed sampling algorithm we proposed built-in. Users can use this tool visualize and analyze the network through user interactions. Extensive case study using the UCI KDD Movie network demonstrates how users can apply this tool to explore the heterogeneous information networks.