Sciweavers

Share
WAW
2007
Springer

Clustering Social Networks

10 years 5 months ago
Clustering Social Networks
Social networks are ubiquitous. The discovery of close-knit clusters in these networks is of fundamental and practical interest. Existing clustering criteria are limited in that clusters typically do not overlap, all vertices are clustered and/or external sparsity is ignored. We introduce a new criterion that overcomes these limitations by combining internal density with external sparsity in a natural way. An algorithm is given for provably finding the clusters, provided there is a sufficiently large gap between internal density and external sparsity. Experiments on real social networks illustrate the effectiveness of the algorithm.
Nina Mishra, Robert Schreiber, Isabelle Stanton, R
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where WAW
Authors Nina Mishra, Robert Schreiber, Isabelle Stanton, Robert Endre Tarjan
Comments (0)
books