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增强多层网络心理地图保持效果的力引导布局算法

A Force-Directed Layout Algorithm for Enhancing the Mental Map Preservation in Multilayer Networks

  • 摘要: 为了增强多层网络可视化中网络布局的心理地图保持效果, 减轻读者在跨层分析任务中的认知负担, 提出一种应用于切片式多层网络可视化的力引导布局算法. 首先计算节点副本间的单向吸引系数; 然后根据单向吸引系数和各节点副本的当前位置计算各节点副本的理想位置及距离差; 最后结合距离差损失项、KK算法能量函数和节点副本间距损失项构建损失函数并优化得到布局方案. 通过在10个公开数据集, 其中7个社交网络数据集, 3个遗传网络数据集上, 与同类型算法对比在心理地图保持指标, 即节点移动总距离上的表现, 表明所提算法能够显著增强多层网络布局的心理地图保持效果.

     

    Abstract: To enhance the mental map preservation in multilayer network visualization and reduce the cognitive load of readers in processing cross-layer analysis tasks, a force-directed based layout algorithm is proposed for multilayer network visualization. Firstly, the unidirectional attraction coefficient between node copies is calculated; Then, according to the unidirectional attraction coefficient and the current position of node copies, the ideal position and distance difference is calculated; Finally, the loss function is constructed by combining the loss term of distance difference, the energy function of KK algorithm and the loss term of spacing between nodes. The experimental results on ten public datasets including seven social networks and three genetic networks show that compared with other similar algorithms, the proposed algorithm has better performances in the sum of absolute differences of nodes, which indicates the proposed algorithm can significantly enhance the mental map preservation in multilayer networks.

     

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