%0 Journal Article %1 paper:edachery:1999 %A Edachery, Jubin %A Sen, Arunabha %A Brandenburg, Franz %D 1999 %J Graph Drawing %K clustering graph %P 98--106 %T Graph Clustering Using Distance-k Cliques %U http://dx.doi.org/10.1007/3-540-46648-7_10 %X 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 distance-k cliques, a generalization of the idea of the cliques in graphs. The performance of the clustering algorithm on some large graphs obtained from the archives of Bell Laboratoriesis presented.

@article{paper:edachery:1999, abstract = {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 distance-k cliques, a generalization of the idea of the cliques in graphs. The performance of the clustering algorithm on some large graphs obtained from the archives of Bell Laboratoriesis presented.}, added-at = {2009-03-27T10:39:22.000+0100}, author = {Edachery, Jubin and Sen, Arunabha and Brandenburg, Franz}, biburl = {https://www.bibsonomy.org/bibtex/26e4a26a0d92351b8aba038966d3be5df/mschuber}, description = {SpringerLink - Book Chapter}, interhash = {666c09a977ea5c7497f27034def5734a}, intrahash = {6e4a26a0d92351b8aba038966d3be5df}, journal = {Graph Drawing}, keywords = {clustering graph}, pages = {98--106}, timestamp = {2009-03-27T10:39:22.000+0100}, title = {Graph Clustering Using Distance-k Cliques}, url = {http://dx.doi.org/10.1007/3-540-46648-7_10}, year = 1999 }