Hierarchical Graph Clustering using Node Pair Sampling

Code

• github.com/tbonald/paris
  OfficialIn papernone★ 0
• github.com/Sharpenb/python_paris
  OfficialIn papernone★ 0
• github.com/dakrod/bottom_up_hcd
  none★ 0

Abstract

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 illustrated on both synthetic and real datasets.

Tasks

Reproductions