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Egocentric Storylines for Visual Analysis of Large Dynamic Graphs

机译:用于对大动态图形的视觉分析的Egocentric故事情节

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Large dynamic graphs occur in many fields. While overviews are often used to provide summaries of the overall structure of the graph, they become less useful as data size increases. Often analysts want to focus on a specific part of the data according to domain knowledge, which is best suited by a bottom-up approach. This paper presents an egocentric, bottom-up method to exploring a large dynamic network using a storyline representation to summarise localized behavior of the network over time.
机译:许多领域发生了大动态图。虽然概述通常用于提供图形的整体结构的总结,但它们变得不太有用,因为数据大小增加。分析师通常希望根据域知识专注于数据的特定部分,这是最适合自下而上的方法。本文介绍了一种使用Storyline表示探索大型动态网络的自动成形,用于汇总网络的本地化行为随时间。

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