ITeM：独立时序模体对时序网络的概括和比较
ITeM: Independent Temporal Motifs to Summarize and Compare Temporal Networks
摘要：
网络是表示各种复杂系统的基本和灵活的方式。许多领域，如通信，引用，采购，生物学，社交媒体和运输，可以建模为一组实体及其关系。时间网络是一般网络的特殊化，其中系统的时间演化与实体和关系的结构一样重要。我们提出了独立的时间模体（ITeM）的时间图从不同的领域进行表征。ITeM是边不相交的时间图案，可以用来模拟图的结构和演化。对于给定的时间图，我们生成ITeM频率的特征向量，并将此分布应用于测量时间图相似性的任务。我们表明，ITeM具有更高的准确性比其他基序频率为基础的方法。我们定义了各种指标的基础上ITeM，揭示了显着的时间网络的属性。我们还提出了重要性采样作为一种有效地估计ITeM计数的方法。我们评估我们的方法合成和真实的时间网络。
英文摘要：
Networks are a fundamental and flexible way of representing various complex systems. Many domains such as communication, citation, procurement, biology, social media, and transportation can be modeled as a set of entities and their relationships. Temporal networks are a specialization of general networks where the temporal evolution of the system is as important to understand as the structure of the entities and relationships. We present the Independent Temporal Motif (ITeM) to characterize temporal graphs from different domains. The ITeMs are edge-disjoint temporal motifs that can be used to model the structure and the evolution of the graph. For a given temporal graph, we produce a feature vector of ITeM frequencies and apply this distribution to the task of measuring the similarity of temporal graphs. We show that ITeM has higher accuracy than other motif frequency-based approaches. We define various metrics based on ITeM that reveal salient properties of a temporal network. We also present importance sampling as a method for efficiently estimating the ITeM counts. We evaluate our approach on both synthetic and real temporal networks.
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