A Graph Similarity Relation Defined by Graph Transformation

Pfaltz, John L.

doi:10.1109/icamcs.net46018.2018.00035

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“…It has been proposed that a formal definition of "similarity" must require the similar networks to have isomorphic interiors[19] 11. Our code generates artificial node names of the form 'A0, B0, .…”

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confidence: 99%

A Set-theoretic Approach to Modeling Network Structure

Pfaltz¹

2021

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Three computer algorithms are presented. One reduces a network $\CALN$ to its interior, $\CALI$. Another counts all the triangles in the network, and the last randomly generates networks similar to $\CALN$ given just its interior $\CALI$. But these algorithms are not the usual numeric programs that manipulate a matrix representation of the network; they are set-based. Union and meet are essential binary operators; contained_in is the basic relational comparator. The interior $\CALI$ is shown to have desirable formal properties and to provide an effective way of revealing ``communities'' in social networks.

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confidence: 99%