On modularity clustering

doi:10.1109/TKDE.2007.190689

On modularity clustering

2008-02-01

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DOI：10.1109/TKDE.2007.190689

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Abstract

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Modularity is a recently introduced quality measure for graph clusterings. It has immediately received considerable attention in several disciplines, particularly in the complex systems literature, although its properties are not well understood. We study the problem of finding clusterings with maximum modularity, thus providing theoretical foundations for past and present work based on this measure. More precisely, we prove the conjectured hardness of maximizing modularity both in the general case and with the restriction to cuts and give an Integer Linear Programming formulation. This is complemented by first insights into the behavior and performance of the commonly applied greedy agglomerative approach.

Keywords:

graph clustering

graph partitioning

modularity

community structure

greedy algorithm

On modularity clustering

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