Induced Edge Samplings and Triangle Count Distributions in Large Networks
This work focuses on distributions of triangle counts per node and edge, as a means for network description, analysis, model building and other tasks. The main interest is in estimating these distributions through sampling, especially for large networks. Suitable sampling schemes for this are introduced and also adapted to the situations where network access is restricted or streaming data of edges are available. Estimation under the proposed sampling schemes is studied through several methods, and examined on simulated and real-world networks.
KeywordsTriangles Random sampling Distribution estimation Static and streaming graphs Power laws
- 3.Bar-Yossef, Z., Kumar, R., Sivakumar, D.: Reductions in streaming algorithms, with an application to counting triangles in graphs. In: Proceedings of the 13th Annual ACM-SIAM SODA, pp. 623–632 (2002)Google Scholar
- 5.Buriol, L.S., Frahling, G., Leonardi, S., Marchetti-Spaccamela, A., Sohler, C.: Counting triangles in data streams. In: Proceedings of the 25th ACM SIGMOD-SIGACT-SIGART PODS, pp. 253–262 (2006)Google Scholar