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Commute Times, Discrete Green's Functions and Graph Matching

机译:通勤时间,离散格林函数和图匹配

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This paper describes a graph-spectral method for simplifying the structure of a graph. Our starting point is the lazy random walk on the graph, which is determined by the heat-kernel of the graph and can be computed from the spectrum of the graph Laplacian. We characterise the random walk using the commute time between nodes, and show how this quantity may be computed from the Laplacian spectrum using the discrete Green's function. Our idea is to augment the graph with an auxiliary node which acts as a heat source. We use the pattern of commute times from this node to decompose the graph into a sequence of layers. These layers can be located using the Green's function. We exploit this decomposition to develop a layer-by-layer graph-matching strategy. The matching method uses the commute time from the auxiliary node as a node-attribute.
机译:本文介绍了一种用于简化图结构的图谱方法。我们的出发点是图上的惰性随机游动,它是由图的热核确定的,可以从图拉普拉斯算子的频谱中计算出来。我们使用节点之间的通勤时间来表征随机游动,并说明如何使用离散格林函数从拉普拉斯频谱中计算出该数量。我们的想法是使用辅助节点作为热源来扩充图。我们使用此节点的通勤时间模式将图分解为一系列图层。可以使用Green的功能来定位这些图层。我们利用这种分解来开发逐层图匹配策略。匹配方法使用来自辅助节点的通勤时间作为节点属性。

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