论文标题
数据压缩以选择适当的动态网络表示
Data compression to choose a proper dynamic network representation
论文作者
论文摘要
动态网络数据现在可以在各种上下文和域中获得。存在几种表示形式主义来表示动态网络，但是没有众所周知的方法可以选择一种表示给定数据集的表示。在本文中，我们提出了一种基于数据压缩的方法，以在三个最重要的表示之间进行选择：快照，链接流和间隔图。我们将方法应用于综合和真实数据集上，以显示该方法及其可能的应用程序的相关性，例如在面对新数据集时选择适当的表示形式，并以有效的方式存储动态网络。
Dynamic network data are now available in a wide range of contexts and domains. Several representation formalisms exist to represent dynamic networks, but there is no well-known method to choose one representation over another for a given dataset. In this article, we propose a method based on data compression to choose between three of the most important representations: snapshots, link streams and interval graphs. We apply the method on synthetic and real datasets to show the relevance of the method and its possible applications, such as choosing an appropriate representation when confronted to a new dataset, and storing dynamic networks in an efficient manner.
