Stable visualization of connected components in dynamic graphs

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
E. D. Giacomo, W. Didimo, M. Kaufmann, G. Liotta
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引用次数: 2

Abstract

One of the primary goals of many systems for the visual analysis of dynamically changing networks is to maintain the stability of the drawing throughout the sequence of graph changes. We investigate the scenario where the changes are determined by a stream of events, each being either an edge addition or an edge removal. The visualization must be updated immediately after each new event is received. Our main goal is to provide the user with an intuitive visualization that highlights the different connected components of the graph while preserving the user’s mental map after each event. The drawing stability is measured in terms of changes in the orthogonal relationships between vertices of two consecutive drawings. We describe two different visualization models, one for the 1-dimensional space and the other for the 2-dimensional space. In both models the connected components are drawn inside rectangular regions. To validate our approach, we report the results of an experimental analysis that compares the drawing stability of the online algorithm with that of an offline algorithm that knows in advance the whole sequence of events. We also present a case study of our online algorithm on a collaboration network.
动态图形中连接组件的稳定可视化
用于动态变化网络的可视化分析的许多系统的主要目标之一是在图形变化的整个序列中保持绘图的稳定性。我们研究了由一系列事件决定变化的场景,每个事件要么是边缘添加,要么是边缘移除。可视化必须在收到每个新事件后立即更新。我们的主要目标是为用户提供直观的可视化,突出显示图形的不同连接组件,同时在每次事件后保留用户的心理地图。绘图稳定性是根据两个连续绘图的顶点之间的正交关系的变化来测量的。我们描述了两种不同的可视化模型,一种用于一维空间,另一种用于二维空间。在这两个模型中,连接的零部件都绘制在矩形区域内。为了验证我们的方法,我们报告了一项实验分析的结果,该分析比较了在线算法和离线算法的绘图稳定性,离线算法提前知道整个事件序列。我们还介绍了我们在协作网络上的在线算法的案例研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Information Visualization
Information Visualization COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
5.40
自引率
0.00%
发文量
16
审稿时长
>12 weeks
期刊介绍: Information Visualization is essential reading for researchers and practitioners of information visualization and is of interest to computer scientists and data analysts working on related specialisms. This journal is an international, peer-reviewed journal publishing articles on fundamental research and applications of information visualization. The journal acts as a dedicated forum for the theories, methodologies, techniques and evaluations of information visualization and its applications. The journal is a core vehicle for developing a generic research agenda for the field by identifying and developing the unique and significant aspects of information visualization. Emphasis is placed on interdisciplinary material and on the close connection between theory and practice. This journal is a member of the Committee on Publication Ethics (COPE).
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