Analysis of the Neighborhood Pattern Similarity Measure for the Role Extraction Problem
Analysis of the Neighborhood Pattern Similarity Measure for the Role Extraction Problem
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DOI：
10.1137/20m1358785
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发表时间：
2020-09
期刊：
影响因子：
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通讯作者：
Melissa Marchand;K. Gallivan;Wen Huang;P. Dooren
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文献类型：
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作者：
Melissa Marchand;K. Gallivan;Wen Huang;P. Dooren
在本文中，我们分析了一种间接的方法，称为邻域模式相似度方法，来解决所谓的大规模图的角色提取问题。该方法基于节点相似性矩阵的初步构建，该矩阵允许在第二阶段使用适当的聚类技术将分配给具有相同角色的节点分组在一起。该分析建立在理想图的概念之上，其中所有具有相同角色的节点在结构上也是等效的。
In this paper we analyze an indirect approach, called the Neighborhood Pattern Similarity approach, to solve the so-called role extraction problem of a large-scale graph. The method is based on the preliminary construction of a node similarity matrix which allows in a second stage to group together, with an appropriate clustering technique, the nodes that are assigned to have the same role. The analysis builds on the notion of ideal graphs where all nodes with the same role, are also structurally equivalent.