Abstract
Clustering nodes in a graph is a useful general technique in data mining of large network data sets. In this context, Newman and Girvan 9 recently proposed an objective function for graph clustering called the Q function which allows automatic selection of the number of clusters. Empirically, higher values of the Q function have been shown to correlate well with good graph clusterings. In this paper we show how optimizing the Q function can be reformulated as a spectral relaxation problem and ...
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