Corpus ID: 46940726

Hierarchical Graph Clustering using Node Pair Sampling

@article{Bonald2018HierarchicalGC,
  title={Hierarchical Graph Clustering using Node Pair Sampling},
  author={T. Bonald and B. Charpentier and Alexis Galland and Alexandre Hollocou},
  journal={ArXiv},
  year={2018},
  volume={abs/1806.01664}
}
  • T. Bonald, B. Charpentier, +1 author Alexandre Hollocou
  • Published 2018
  • Computer Science
  • ArXiv
  • We present a novel hierarchical graph clustering algorithm inspired by modularity-based clustering techniques. The algorithm is agglomerative and based on a simple distance between clusters induced by the probability of sampling node pairs. We prove that this distance is reducible, which enables the use of the nearest-neighbor chain to speed up the agglomeration. The output of the algorithm is a regular dendrogram, which reveals the multi-scale structure of the graph. The results are… CONTINUE READING

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