用多层次聚类法完成的大规模关系图的可视化

提出了一种新的大规模图形可视化技术.它可显示含有几万个接点和边的大规模关系图.为了完成对图形的抽象化。一个多层次的聚类图形从原始的大规模关系图中抽取了出来.这种抽取是建立在大规模关系图的内在结构基础上来完成的.一种递规封入式的几何划分算法被应用来完成对几何空间的优化,在具体的制图技术上,使用了一种用力导向布局算法和环形制图法相结合的新方法,从而完成了对显示空间的优化和美擘上的优化.同时也讨论了相关的人机交互技术,所采用的人机交互算法不仅能让使用者从上到下层次式地浏览整个聚类图形。同时也能提供多层次聚类图形的并行浏览.动画技术也同时被运用,以保护使用者的精神图不被打乱.

Large Graph Visualization by Hierarchical Clustering

This paper proposes a new technique for visualizing large graphs of several ten thousands of vertices and edges.To achieve a graph abstraction,a hierarchical clustered graph is extracted from a general large graph based on the community structures discovered in the graph.An enclosure geometrical partitioning algorithm is then applied to achieving the space optimization.For graph drawing,it uses a combination of spring-embbeder and circular drawing algorithms that archives the goal of optimization of display space and aesthetical niceness.The paper also discusses an interaction mechanism accompanied with the layout solution.The interaction not only allows users to navigate hierarchically through the entire clustered graph,but also provides a way to navigate multiple clusters concurrently.Animation is also implemented to preserve user mental maps during the interaction.