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Hi, guys, this looks like a great start of a powerful knowledge graph embedding libraray! Thanks for sharing it!
My question is: many practical applications involve knowledge graphs with mixture of structured (knowledge graph itself) and unstructured literal data (attributes like description, name, date, and etc). Do you have any plan to support literal-enhanced embedding like LiteralE as well? thanks.
The other interesting development is Graph-BERT, where attention on local subgraph is used instead of GCN. It seems to be more scalable. Will you coonsider supporting it?
ps. both algorithms already have their source code available right now.
The text was updated successfully, but these errors were encountered:
Hi, guys, this looks like a great start of a powerful knowledge graph embedding libraray! Thanks for sharing it!
My question is: many practical applications involve knowledge graphs with mixture of structured (knowledge graph itself) and unstructured literal data (attributes like description, name, date, and etc). Do you have any plan to support literal-enhanced embedding like LiteralE as well? thanks.
The other interesting development is Graph-BERT, where attention on local subgraph is used instead of GCN. It seems to be more scalable. Will you coonsider supporting it?
ps. both algorithms already have their source code available right now.
The text was updated successfully, but these errors were encountered: