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基于力导向算法优化的有向加权网络数据的可视分析 被引量:2

Visual Analytics of Directed Weighted Graph Based on Optimized Force-Directed Layout Algorithms
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摘要 复杂关系网络数据的可视分析多采用有向加权的节点-连接图布局。由于节点间的连接关系为多属性数据,传统的布局绘制算法难以完整地呈现数据间的组织结构。本文通过对力导向物理学模型进行优化设计,结合多通道视觉编码设计,完成对复杂关系网络数据可视化的绘制。相比较传统的节点-连接图布局,本算法在呈现多属性网络数据时具有更好的认知效能。 Visual analysis of complex relational network data mostly uses directed weighted node-join graph layout. Because the connection relationship between nodes is multi-attribute data,the traditional layout rendering algorithm is difficult to fully present the organizational structure of data. By optimizing the force-directed physical model and combining with the design of multi-channel visual coding,this paper completes the visualization of complex relational network data. Compared with the traditional node-connection graph layout,the algorithm has better cognitive performance in presenting multi-attribute network data.
作者 巫滨 WU Bin(School of Art&Design,Henan University of Science&Technology,Luoyang 471000,China)
出处 《现代信息科技》 2019年第19期88-92,共5页 Modern Information Technology
基金 河南省科技厅软科学项目基金:我省人机交互创新研究(项目编号:142400410036)资助 河南科技大学教育教学改革课题:基于多维教学数据仓库的可视化课程评析方法研究(项目编号:2017JGYB61)的阶段性研究成果
关键词 可视分析 复杂关系网络 力导向布局算法 visual analytics complex relational network FDLA(Force-Directed Layout Algorithms)
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