Fast top- similarity search in large dynamic attributed networks.

•A similarity search algorithm for attributed networks that combines the structure similarity and the attribute similarity into one single metric.•A single-source path sampling procedure for sampling single source paths, which is efficient and have a theoretic bound on the sample size.•Two dynamic updating schemes for maintaining similarity scores in response to batches of updates of nodes, edges and attributes.•Experimental results show that our proposed method achieves better convergence performance, runs faster than Panther.