Large graph layout optimization based on vision and computational efficiency: a survey

作     者：Shuhang Zhang Ruihong Xu Yining Quan 

作者机构：School of Computer Science and TechnologyXidian UniversityXi’anChina 

出 版 物：《Visual Intelligence》 (视觉智能(英文))

年 卷 期：2023年第1卷第1期

页      面：237-248页

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Natural Science Foundation of China(No.61872432) 

主　　题：Large graph layout Node-link diagram Optimization Visualization 

摘      要：Graph layout can help users explore graph data ***,when handling large graph data volumes,the high time complexity of the layout algorithm and the overlap of visual elements usually lead to a significant decrease in analysis efficiency and user *** computing speed and improving visual quality of large graph layouts are two key approaches to solving these *** surveys are mainly conducted from the aspects of specific graph type,layout techniques and layout evaluation,while seldom concentrating on layout *** paper reviews the recent works on the optimization of the visual and computational efficiency of graphs,and establishes a taxonomy according to the stage when these methods are implemented:pre-layout,in-layout and *** pre-layout methods focus on graph data compression techniques,which involve graphfiltering and graph *** in-layout approaches optimize the layout process from computing architecture and algorithms,where deep learning techniques are also *** mapping and interactive layout adjustment are post-layout optimization *** survey reviews the current research on large graph layout optimization techniques in different stages of the layout design process,and presents possible research challenges and opportunities in the future.