Loading data from dataframe to bipartite graph

❓ Questions & Help

I am new into pytorch_geometric and i am trying to use BipartiteData class to load data from dataframe which looks something like this:

weight_of_edge : means how many times customer_id order from vendor_id

Wanted to know if I passing correctly the data from my dataframe to the BipartitData class ?

This are my variables defined from dataframe to fed BipartitData: weight = (torch.Tensor(df['weight_of_edg'].values)).long() customer_id = (torch.Tensor(df['customer_id'].values)).long() vendor_id = (torch.Tensor(df['vendor_id'].values)).long() edge_index = torch.Tensor((np.vstack((customer_id, vendor_id)))).long()

Finally i passed this way: data = BipartiteData(edge_index, customer_id, vendor_id) data.edge_attr = weight

Is this okay? Thanks you very much ! keep with the excellent job 😃 !

[rusty1s]

Sorry for the late reply.

1. If you rely on learned embeddings for certain node types, you have to train any new embedding as well. You can either do that by re-training your model with the new node (with can become expensive), or only train the embedding for the new node while holding all other parameters fixed.
2. Yes, I think this is indeed hybrid as well, but I’m not aware of any paper explaining that in detail.

[rusty1s]

It’s embedding is not trained, and the recommendation is likely going to be random 😃