Adaptive Visualization for Large Tree Graph

Abstract

We propose an adaptive visualization technique for a large-scale hierarchical dataset within limited display space. A hierarchical dataset has nodes and links that represent the parent-child relationship. These nodes and links are described using graphics primitives. When the number of these primitives is large, it is difficult to recognize the structure of the hierarchical data, because many primitives are overlapped within a limited region. In this context, we propose an adaptive visualization technique for hierarchical datasets. The proposed technique selects an appropriate graph style based on the density of the nodes. In addition, we demonstrate the effectiveness of the proposed method by applying it to perfect binary trees and large branch-and-bound trees.