AHD-SLE

A PyTorch implementation for the paper below: AHD-SLE: Anomalous Hyperedge Detection on Hypergraph Symmetric Line Expansion

1. Code Structure

• data/ : under this folder, we provide several hypergraph datasets

  • dblp, iAF1260b, iJO1366, reverb, uspto
  • *.edges.neg : negative hyperedge dataset, format: node_id, hyperedge_id
  • *.edges.pos : positive hyperedge dataset, format: node_id, hyperedge_id
  • *.npz : node feature, it a sparse matrix

• layers.py: standard GCN layers

• logutil.py: logging function

• main.py: the running script

• models.py: AHD-SLE model implementations

• SLE.py: the SLE transformation script

• utils.py: auxiliary functions

2. Running AHD-SLE

# select a dataset from dblp, iAF1260b, iJO1366, reverb, uspto
python main.py --dataset [DATASET]