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PKDD
2015
Springer

Generalized Modularity for Community Detection

4 years 7 months ago
Generalized Modularity for Community Detection
Detecting the underlying community structure of networks is an important problem in complex network analysis. Modularity is a well-known quality function introduced by Newman, that measures how vertices in a community share more edges than what would be expected in a randomized network. However, this limited view on vertex similarity leads to limits in what can be resolved by modularity. To overcome these limitations, we propose a generalized modularity measure called GM which has a more sophisticated interpretation of vertex similarity. In particular, GM also takes into account the number of longer paths between vertices, compared to what would be expected in a randomized network. We also introduce a unified version of GM which detects communities of unipartite and (near-)bipartite networks without knowing the structure type in advance. Experiments on di↵erent synthetic and real data sets, demonstrate GM performs strongly in comparison to several existing approaches, particularly f...
Mohadeseh Ganji, Abbas Seifi, Hosein Alizadeh, Jam
Added 16 Apr 2016
Updated 16 Apr 2016
Type Journal
Year 2015
Where PKDD
Authors Mohadeseh Ganji, Abbas Seifi, Hosein Alizadeh, James Bailey, Peter J. Stuckey
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