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作 者:巫滨 曹卫群[1] Wu Bin;Cao Weiqun(School of Information Science and Technology, Beijing Forestry University, Beijing 100083;School of Art and Design , Henan University of Science and Technology, Luoyang 471003)
机构地区:[1]北京林业大学信息学院,北京100083 [2]河南科技大学艺术与设计学院,洛阳471003
出 处:《计算机辅助设计与图形学学报》2017年第10期1807-1815,共9页Journal of Computer-Aided Design & Computer Graphics
基 金:中央高校基本科研业务费专项资金资助(2015ZCQ-XX);河南省科技厅软科学研究基金(142400410036)
摘 要: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;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,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.In the light of misrecognition which caused by over-stretched and over-deviation of cluster curves during 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 skeleton for each cluster.Secondly,the size of each cluster was taken into consideration to adjust the repel force between 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 value 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
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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