Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning. (arXiv:2210.10643v1 [cs.LG])

Subgraph similarity search, one of the core problems in graph search,
concerns whether a target graph approximately contains a query graph. The
problem is recently touched by neural methods. However, current neural methods
do not consider pruning the target graph, though pruning is critically
important in traditional calculations of subgraph similarities. One obstacle to
applying pruning in neural methods is {the discrete property of pruning}. In
this work, we convert graph pruning to a problem of node relabeling and then …

arxiv computation graph pruning