How to calculate similarity between the two graphs?

[smith-co]

I have to learn similarity between graphs using deep learning. I have many samples (~500k) of graphs. Graphs have ~5000 nodes and ~4000 edges in the average.

How can I compute similarity score between two graphs? I am thinking:

• convert graphs into vectors using Graph2Vec embedding
• then compare them using various similarity calculating techniques like cosine similarity.

I would really appreciate if I can get some feedback whether this is the correct way to approach this problem or not.

[danielegrattarola]

Moved this to the Discussions section as it is an open-ended question.

Your approach looks reasonable to me, did you have a particular doubt?

[smith-co]

Thanks for your response @danielegrattarola. I am not expert in the GNN domain.

So would be curious to know how would Graph2Vec embedding would work instead of generating the embedding using GCN or GAT as an example.

[dylanfox5]

Hello - is there any example of this use case? I find myself in a similar situation here. Any further guidance would be appreciated. Thanks!