Figure 1: The performance of different methods in synthetic networks.
From: A multi-similarity spectral clustering method for community detection in dynamic networks
(a,b) Normalized mutual information and the sum of the squared errors of different methods at 10 snapshots in synthetic networks, where the parameter z is 5, the average degree of each node is 16 and at each snapshot, 3 nodes change their cluster membership. (c,d) Performance for a single contraction event with 1000 nodes over 10 snapshots; the nodes have a mean degree of 15, a maximum degree of 50, and a mixing parameter value of μ = 0, which controls the overlapping among communities. Notice that the x-axes show the snapshots.
