平行坐标系聚类数据的力导向分段骨骼绑定绘制

摘要

In the light of misrecognition which caused by over-stretched and over-deviation of cluster curves dur-ing edge bundling in parallel coordinates plot, we proposed a force-directed skeleton-based bundling method (FDSBB) for Clustering data. Firstly, a optimized force-directed algorithm was used to form the layout of skele-ton for each cluster. Secondly, the size of each cluster was taken into consideration to adjust the repel force be-tween clusters, so the offsets of all clusters were transferred to the minority. Finally, we developed poly-skeleton to bundle the cluster in a band-form, which mapping the distribution attributes of clustering data (such as the val-ue of the cluster center, correlation of clustering data, etc) more objectively. Experimental results show that FDSBB method could apparently improve the visual performance of clustering data in parallel coordinates.%针对现有平行坐标系聚类数据在边绑定时线束可能过度弯曲和位置偏移导致用户对数据分布特征的视觉r认知产生曲解的问题提出基于力导向分段式骨骼布局的边绑定方法.首先通过优化的力场模型完成簇间分离布局;r然后建立簇内数据量与线束偏移量的负向关联将簇间分离时线束的移动量调整到规模较小的簇;最后采用分段式r骨骼作为簇内线束收敛的基准生成两端快速收敛、中间呈带状的线束形态以改善整体绘制效果.实验结果表明r该方法可以明显地改善视图对聚类中心值、数据离散度等数据分布特征表达的准确性以及视图的整体绘制效果.