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Hasse diagram based algorithm for continuous temporal subgraph query in graph stream

机译:图流中基于Hasse图的连续时间子图查询算法

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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.
机译:连续子图模式匹配是传统子图模式匹配的扩展,并成为引起越来越多兴趣的主题。它需要近乎实时的响应,并用于许多应用中,例如,社交网络中的异常监视,网络中的网络攻击监视。随着动态图随时间变化,考虑了时间子图模式(即,边缘具有时间关系)。在本文中,引入了Hasse图来表示查询图的时间关系。然后设计了Hasse-cache结构,并提出了基于Hasse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验证。我们对真实数据集的实验表明,与以前的方法相比,该算法的速度提高了10倍。

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