Graph clustering using multiway ratio cut (Software demonstration)
Identifying the natural clusters of nodes in a graph and treating them as supernodes or metanodes for a higher level graph (or an abstract graph) is a technique used for the reduction of visual complexity of graphs with a large number of nodes. In this paper we report on the implementation of a clustering algorithm based on the idea of ratio cut, a well known technique used for circuit partitioning in the VLSI domain. The algorithm is implemented in WINDOWS95/NT environment. The performance of the clustering algorithm on some large graphs obtained from the archives of Bell Laboratories is presented.
- 1.R. Sablowski and A. Frick, “Automatic Graph Clustering,” Proceedings of Graph Drawing'96, Berkeley, California, September,1996.Google Scholar
- 2.U. Dogrusoz, B. Madden and P. Madden, “Circular Layout in the Graph Layout Toolkit,” Proceedings of Graph Drawing'96, Berkeley, California, September,1996.Google Scholar
- 3.P. Eades, “Multilevel Visualization of Clustered Graphs,” Proceedings of Graph Drawing'96, Berkeley, California, September,1996.Google Scholar
- 6.D. Kimmelman, B. Leban, T. Roth, D. Zernik “Dynamic Graph Abstraction for Effective Software Visualization,” The Australian Computer Journal, vol. 27, no. 4, pp.129–137, Nov 1995.Google Scholar
- 7.F. J. Brandenburg, M. Himsolt and K. Skodinis, “Graph Clustering: Circles of Cliques,” submitted to Graph Drawing'97.Google Scholar