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Method for identifying network similarity by matching neighborhood topology

机译:通过匹配邻居拓扑识别网络相似度的方法

摘要

A method of computing a measure of similarity between nodes of first and second networks is described. In particular, sets of pairwise scores are computed to find nodes in the individual networks that are good matches to one another. Thus, a pairwise score, referred to as Rij, is computed for a node i in the first network and a node j in the second network. Similar pairwise scores are computed for each of the nodes in each network. The goal of this process is to identify node pairs that exhibit high Rij values. According to the technique described herein, the intuition is that nodes i and j are a good match if their neighbors are a good match. This technique produces a measure of “network similarity.” If node feature data also is available, the intuition may be expanded such that nodes i and j are considered a good match if their neighbors are a good match (network similarity) and their node features are a good match (node similarity). Node feature data typically is domain-specific. Using the similarity scores, a common subgraph between the first and second networks then can be computed.
机译:描述了一种计算第一网络和第二网络的节点之间的相似性度量的方法。特别地,计算成对分数集以在各个网络中找到彼此良好匹配的节点。因此,为第一网络中的节点i和第二网络中的节点j计算成对分数,称为R ij 。为每个网络中的每个节点计算相似的成对分数。此过程的目标是确定具有高R ij 值的节点对。根据本文描述的技术,直觉是节点i和j如果它们的邻居是良好匹配则是良好匹配。这种技术可以衡量“网络相似性”。如果节点特征数据也可用,则可以扩展直觉,使得如果节点i和j的邻居是良好匹配(网络相似性)并且其节点特征是良好匹配(节点相似性),则认为节点i和j是良好匹配。节点要素数据通常是特定于域的。使用相似性分数,则可以计算出第一网络和第二网络之间的公共子图。

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