图流中连续时间子图查询的Hasse图算法

Xiaoli Sun, Yusong Tan, Q. Wu, Jing Wang
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引用次数: 5

摘要

连续子图模式匹配是传统子图模式匹配的扩展,是近年来越来越受到关注的课题。它要求近乎实时的响应,被广泛应用于社交网络中的异常监测、网络网络中的网络攻击监测等领域。由于动态图随时间变化,考虑了时间子图模式(即边具有时间关系)。本文引入Hasse图来表示查询图的时间关系。然后设计了哈希缓存结构,提出了一种基于哈希图的连续时间子图模式匹配算法。该算法利用动态图的概率来减少中间结果,可以同时实现拓扑匹配和时间关系的验证。我们对真实数据集的实验表明,所提出的算法比以前的方法有10倍的加速。
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Hasse diagram based algorithm for continuous temporal subgraph query in graph stream
Continuous subgraph pattern matching is an extension of the traditional subgraph pattern matching and becoming a subject that attracts increasing interest. It requires the near real-time responses and is used in many applications, for example, abnormal monitoring in social networks, cyber attacks monitoring in cyber networks. As the dynamic graph changes with time, the temporal subgraph pattern (i.e., the edges have temporal relation) is considered. In this paper, the Hasse diagram is introduced to represent the temporal relation of the query graph. Then we design the Hasse-cache structure, and propose a continuous temporal subgraph pattern matching algorithm based on the Hasse diagram. The algorithm uses the probability of dynamic graph to reduce the intermediate results, and can implement the matching of topology and the verification of temporal relation simultaneously. Our experiments with real-world datasets show that the proposed algorithm has 10x speedups over the previous approaches.
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