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20062024
most citedClustering via Hypergraph Modularity

83 citations · 346 across the 78 of their papers we have counts for

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Showing 2017Show all

6 papers · 1 filter

math.PR2017

Local Clustering Coefficient of Spatial Preferential Attachment Model

Lenar Iskhakov, Bogumil Kaminski, Maksim Mironov +2

In this paper, we study the clustering properties of the Spatial Preferential Attachment (SPA) model. This model naturally combines geometry and preferential attachment using the n…

math.CO2017

Common adversaries form alliances: modelling complex networks via anti-transitivity

Anthony Bonato, Ewa Infeld, Hari Pokhrel +1

Anti-transitivity captures the notion that enemies of enemies are friends, and arises naturally in the study of adversaries in social networks and in the study of conflicting natio…

math.CO2017

How many zombies are needed to catch the survivor on toroidal grids?

Pawel Pralat

In Zombies and Survivors, a set of zombies attempts to eat a lone survivor loose on a given graph. The zombies randomly choose their initial location, and during the course of the…

math.CO2017

Subhypergraphs in non-uniform random hypergraphs

Megan Dewar, John Healy, Xavier Pérez-Giménez +4

In this paper we focus on the problem of finding (small) subhypergraphs in a (large) hypergraph. We use this problem to illustrate that reducing hypergraph problems to graph proble…

math.PR2017

Modularity of complex networks models

Liudmila Ostroumova Prokhorenkova, Pawel Pralat, Andrei Raigorodskii

Modularity is designed to measure the strength of division of a network into clusters (known also as communities). Networks with high modularity have dense connections between the…

math.CO2017

Clique colourings of geometric graphs

Colin McDiarmid, Dieter Mitsche, Pawel Pralat

A clique colouring of a graph is a colouring of the vertices such that no maximal clique is monochromatic (ignoring isolated vertices). The least number of colours in such a colour…