With the proliferation of temporal graph data, there is a growing demand for analyzing information propagation patterns during graph evolution. Existing graph analysis systems, mostly based on static snapshots, struggle to effectively capture information flows along the temporal dimension. To address this challenge, we introduce ChronoConnect, a novel system that enables tracking temporal pathways in temporal graph, especially beneficial to downstream mining tasks, e.g., understanding what are the critical pathways in propagating information towards a specific group of vertices. Built on ChronoConnect, users can conveniently configure and execute a variety of temporal traversal algorithms to efficiently analyze information diffusion processes under time constraints. Moreover, ChronoConnect utilizes parallel processing to tackle the explosive size-growth of evolving graphs. We showcase the effectiveness and enhanced performance of ChronoConnect through the implementation of algorithms that track pathways along highly dynamic vertices in temporal graphs. Furthermore, we offer an interactive user interface for graph visualization and query result exploration. We envision ChronoConnect to become a powerful tool for users to examine how information spreads over a temporal graph.

翻译：随着时序图数据的激增，分析图演化过程中信息传播模式的需求日益增长。现有的图分析系统大多基于静态快照，难以有效捕捉沿时间维度的信息流。为应对这一挑战，我们提出了ChronoConnect——一种新颖的系统，能够追踪时序图中的时间路径，尤其有利于下游挖掘任务，例如理解向特定顶点群传播信息的关键路径。基于ChronoConnect，用户可以便捷地配置和执行多种时序遍历算法，以高效分析时间约束下的信息扩散过程。此外，ChronoConnect利用并行处理技术应对演化图数据规模的爆炸性增长。我们通过实现追踪时序图中高度动态顶点路径的算法，展示了ChronoConnect的有效性和优越性能。同时，我们提供了用于图可视化和查询结果探索的交互式用户界面。我们期待ChronoConnect成为用户研究信息在时序图中传播方式的强大工具。