This paper presents a reference data set along with a labeling for graph clustering algorithms, especially for those handling dynamic graph data. We implemented a modification of Iterative Conductance Cutting and a spectral clustering. As base data set we used a filtered part of the Enron corpus. Different cluster measurements, as intra-cluster density, inter-cluster sparseness, and Q-Modularity were calculated on the results of the clustering to be able to compare results from other algorithms. © 2013 Springer-Verlag.
CITATION STYLE
Held, P., & Dannies, K. (2013). Clustering on dynamic social network data. In Advances in Intelligent Systems and Computing (Vol. 190 AISC, pp. 563–571). Springer Verlag. https://doi.org/10.1007/978-3-642-33042-1_60
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