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Node overlap removal in clustered directed acyclic graphs

机译:聚簇有向无环图中的节点重叠去除

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Graph drawing and visualization represent structural information as diagrams of abstract graphs and networks. An important subset of graphs is directed acyclic graphs (DAGs). This paper presents a new E-Spring algorithm, extended from the popular spring embedder model, which eliminates node overlaps in clustered DAGs. In this framework, nodes are modeled as non-uniform charged particles with weights, and a final drawing is derived by adjusting the positions of the nodes according to a combination of spring forces and repulsive forces derived from electrostatic forces between the nodes. The drawing process needs to reach a stable state when the average distances of separation between nodes are near optimal. We introduce a stopping condition for such a stable state, which reduces equilibrium distances between nodes and therefore results in a significantly reduced area for DAG visualization. It imposes an upper bound on the repulsive forces between nodes based on graph geometry. The algorithm employs node interleaving to eliminate any residual node overlaps. These new techniques have been validated by visualizing eBay buyer-seller relationships and has resulted in overall area reductions in the range of 45-79%.
机译:图的绘制和可视化将结构信息表示为抽象图和网络的图。图的重要子集是有向无环图(DAG)。本文提出了一种新的E-Spring算法,该算法是从流行的弹簧嵌入器模型扩展而来的,该算法消除了群集DAG中的节点重叠。在此框架中,将节点建模为具有权重的非均匀带电粒子,并根据弹簧力和从节点之间的静电力得出的排斥力的组合,通过调整节点的位置来得出最终图形。当节点之间的平均间隔距离接近最佳时,绘制过程需要达到稳定状态。我们针对这种稳定状态引入了停止条件,该条件减少了节点之间的平衡距离,因此大大减小了DAG可视化的面积。它基于图几何对节点之间的排斥力施加上限。该算法采用节点交织来消除任何残留的节点重叠。这些新技术已经通过可视化eBay买卖双方关系得到了验证,并导致总面积减少了45-79%。

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