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arXiv · 1702.06363

Stochastic graph Voronoi tessellation reveals community structure

Zsolt I. Lázár·István Papp·Levente Varga·Ferenc Járai-Szabó·Dávid Deritei·Mária Ercsey-Ravasz
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Abstract

Given a network, the statistical ensemble of its graph-Voronoi diagrams with randomly chosen cell centers exhibits properties convertible into information on the network's large scale structures. We define a node-pair level measure called {\it Voronoi cohesion} which describes the probability for sharing the same Voronoi cell, when randomly choosing $g$ centers in the network. This measure provides information based on the global context (the network in its entirety) a type of information that is not carried by other similarity measures. We explore the mathematical background of this phenomenon and several of its potential applications. A special focus is laid on the possibilities and limitations pertaining to the exploitation of the phenomenon for community detection purposes.

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Zsolt I. Lázár, István Papp, Levente Varga, Ferenc Járai-Szabó, Dávid Deritei, Mária Ercsey-Ravasz. 2017-02-21. Stochastic graph Voronoi tessellation reveals community structure. https://doi.org/10.1103/physreve.95.022306

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