Document Object Model (DOM) similarity learning

I would like to know is there a model for generating the embedding of Document Object Model (DOM). DOM is a tree and therefore I suppose a model that handle tree would be a good choice.

The downstream task is to learn DOM similarity.

Given two DOM input, I am thinking to generate the two Dom embeddings emb_dom1, emb_dom2 and then I can take the cosine similarity for the similarity matching.

Any feedback is welcome.

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Stanford have a course on Graph Neural Networks. Not sure if there is a framework out there for it (but there probably is).