We initiate an open-source library for the efficient analysis of temporal graphs. We consider one of the standard models of dynamic networks in which each edge has a discrete timestamp and transition time. Recently there has been a massive interest in analyzing such temporal graphs. Common computational data mining and analysis tasks include the computation of temporal distances, centrality measures, and network statistics like topological overlap, burstiness, or temporal diameter. To fulfill the increasing demand for efficient and easy-to-use implementations of temporal graph algorithms, we introduce the open-source library TGLib, which integrates efficient data structures and algorithms for temporal graph analysis. TGLib is highly efficient and versatile, providing simple and convenient C++ and Python interfaces, targeting computer scientists, practitioners, students, and the (temporal) network research community.
翻译:我们启动了一个开放源码图书馆,以便有效分析时间图。我们考虑了每个边缘都有离散时间戳和过渡时间的动态网络的标准模型之一。最近,人们对分析这种时间图非常感兴趣。共同的计算数据挖掘和分析任务包括计算时间距离、中心度测量和网络统计,如地貌重叠、易爆性或时间直径。为了满足对高效和易于使用的时间图算法的实施日益增长的需求,我们引入了开放源库TGLib,它整合了用于时间图分析的高效数据结构和算法。TGLib高效和多功能,提供了简单和方便的C++和Python界面,针对计算机科学家、从业人员、学生和(时)网络研究界。