多维度空间变换网络拓扑布局方法

Multi-Dimensional Spatial Transformation Network Topology Layout

网络拓扑布局能帮助用户直观地了解分析网络结构.随着网络规模的增大和网络属性的增加,为了兼顾多元网络结构特征的呈现和局部网络的属性关联分析,引导用户进行渐进式探索分析,提出一种多维度空间变换网络拓扑布局方法.首先基于社区特征进行3维布局,呈现网络整体结构特征;基于3维布局和网络属性,对用户筛选的网络结构进行维度空间变换,在2.5维布局中呈现属性和拓扑关联;最后,对用户筛选的单维属性局部网络进行2维布局,通过多样化布局方式呈现局部网络拓扑结构.基于该拓扑布局方法,使用社交网络、脑网络和计算机网络3种数据集进行实验分析,结果证明了所提方法在兼顾结构特征呈现和属性关联分析,以及渐进式探索分析中的有效性.

The network topology layout helps users intuitively understand and analyze the network structure.With the increase of network scale and network attributes,a multi-dimensional spatial transformation network topology layout method is proposed to guide users to conduct progressive exploration analysis and give consideration to the presentation of multivariate network structural features and attribute correlation analysis of local networks.Firstly,the method makes 3-dimensional layout based on the characteristics of the community and presents the overall structure characteristics of the network.Based on the 3-dimensional layout and network attributes,the network structure filtered by users is transformed into dimensional space,and the attributes and topological associations are presented in the 2.5-dimensional layout.Finally,2-dimensional layout is carried out for the single-dimensional attribute local network filtered by users,and the topology of the local network is presented through a diversified layout.Based on this topology layout method,three data sets of social network,brain network and computer network are used for experimental analysis.The results demonstrate the effectiveness of proposed method in both structural feature presentation and attribute association analysis,as well as progressive exploration analysis.