Scalable Discovery of Best Clusters on Large Graphs

@article{Macropol2010ScalableDO,
  title={Scalable Discovery of Best Clusters on Large Graphs},
  author={Kathy Macropol and Ambuj K. Singh},
  journal={PVLDB},
  year={2010},
  volume={3},
  pages={693-702}
}
The identification of clusters, well-connected components in a graph, is useful in many applications from biological function prediction to social community detection. However, finding these clusters can be difficult as graph sizes increase. Most current graph clustering algorithms scale poorly in terms of time or memory. An important insight is that many clustering applications need only the subset of best clusters, and not all clusters in the entire graph. In this paper we propose a new… CONTINUE READING
Highly Cited
This paper has 57 citations. REVIEW CITATIONS

12 Figures & Tables

Topics

Statistics

05101520112012201320142015201620172018
Citations per Year

58 Citations

Semantic Scholar estimates that this publication has 58 citations based on the available data.

See our FAQ for additional information.