流图上的时间约束连续子图搜索
Time Constrained Continuous Subgraph Search over Streaming Graphs
摘要：
诸如社交网络之类的动态应用的日益普及为实时的检测有价值的信息提供了一种有前途的方式。对动态应用中的高速数据进行有效的分析具有重要意义。来自这些动态应用程序的数据可以很容易地建模为流图。在本文中，我们研究的子图（同构）搜索流图数据，遵守时间顺序约束的出现在流中的边缘。我们提出了一个数据结构和算法，以有效地回答子图搜索，并引入优化，以大大减少空间成本，并提出并发管理，以提高系统吞吐量。在真实网络流量数据和合成社交流数据上的大量实验证实了我们的解决方案的效率和有效性。
英文摘要：
The growing popularity of dynamic applications such as social networks provides a promising way to detect valuable information in real time. Efficient analysis over high-speed data from dynamic applications is of great significance. Data from these dynamic applications can be easily modeled as streaming graph. In this paper, we study the subgraph (isomorphism) search over streaming graph data that obeys timing order constraints over the occurrence of edges in the stream. We propose a data structure and algorithm to efficiently answer subgraph search and introduce optimizations to greatly reduce the space cost, and propose concurrency management to improve system throughput. Extensive experiments on real network traffic data and synthetic social streaming data confirms the efficiency and effectiveness of our solution.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
