基于变换的大图点边可视化综述

Survey on Transformation-based Large Graph Visualization

大图可视化是信息可视化领域的前沿课题之一,也是在线社会网络、信息安全、电子商务等热点行业大数据分析的重要支撑技术.基于变换的大图点边可视化方法由于其具有在线处理时间短、可视复杂度低、交互方法灵活多样等优点,近年来在学术界与实际商用系统中得到广泛重视与应用.文中从图可视化的基本概念及其在大图上的关键挑战出发,梳理了基于变换的大图点边可视化方法的典型分类与主要流程;通过详述3类基于变换的大图点边可视化典型方法(图数据抽象、视图变换与视角转换),阐明了不同方案的优缺点与适用场景,并进一步指出了未来工作的可行方向与潜在难点.

Large graph visualization is one of the field. It is also widely accepted as the fundamental hot topics in the information visualization research technique of the big data analytics in industries such as online social networks, information security and e-business. The transformation-based large graph visualization methods have been intensively studied recently due to their advantages over the classical drawing methods in the fast processing speed, low visual complexity and versatile interactions available. They are adopted in many real-world systems and applications. In this paper, we start from the basic concept of large graph visualization and its major challenges. We classify this kind of methods into three types （graph abstraction, view transformation and view point transition） and introduce in detail the representative approaches in each type. Both the pros/cons and the practical usage scenarios are talked about for these methods. Future directions are discussed with respect to the potential technical challenges going ahead.