Analysis of the Neighborhood Pattern Similarity Measure for the Role Extraction Problem
Social and Information Networks
2020-09-28 v1
Abstract
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.
Keywords
Cite
@article{arxiv.2009.11991,
title = {Analysis of the Neighborhood Pattern Similarity Measure for the Role Extraction Problem},
author = {Melissa Marchand and Kyle A. Gallivan and Wen Huang and Paul Van Dooren},
journal= {arXiv preprint arXiv:2009.11991},
year = {2020}
}