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Received:July 24, 2017 Revised:August 09, 2017
Received:July 24, 2017 Revised:August 09, 2017
中文摘要: 大数据背景下，数据对于关系的呈现并不直观，因此人物关系的可视化研究对于抽取隐含知识具有重要的实用价值.从人物关系可视化的边-节点关系及相关信息展示的可视化需求出发，改进了D3.js类库，优化边-节点间的指向关系，便于数据处理，尤其是动态数据处理；采用改进的最短路径算法，能够求解无向图的经指定节点的全部最小环，应用于求取关系图中的人员团体关系；利用D3.js可视化类库的数据驱动特性，实现了具有一定数据交互功能的人物关系图可视化原型.
Abstract:In the background of big data, the relationship presented in data is not intuitive, so the visualization of the relationship is of great practical value for extracting implicit knowledge. Considering the edge-node relationship of the visualization of character relations and the visualization requirements of displaying the relevant information, the D3.js was improved to optimize the links between edges and nodes, which is convenient for data processing, especially for dynamic data. The shortest path algorithm was improved to solve all the minimum rings containing the specified nodes of undirected graphs, and applied to seeking groups in the relationship map. The data-driven features of D3.js visualization library were taken advantage of to display the character relationship map with data exchange function.
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引用文本：
邱秀连,康倩,王峥.人物关系的可视化研究.计算机系统应用,2018,27(4):27-33
QIU Xiu-Lian,KANG Qian,WANG Zheng.Visualization of Character Relations.COMPUTER SYSTEMS APPLICATIONS,2018,27(4):27-33
邱秀连,康倩,王峥.人物关系的可视化研究.计算机系统应用,2018,27(4):27-33
QIU Xiu-Lian,KANG Qian,WANG Zheng.Visualization of Character Relations.COMPUTER SYSTEMS APPLICATIONS,2018,27(4):27-33
