In the end, all embeddings mean the same thing: "they encode some information into a vector"
Depending on your data and the method you use, you can categorize them as token-based, tree-based, graph-based, image-based, etc.
For example, you can encode text data in all the ways you proposed, but depending on the algorithm, you emphasize different aspects. If you use a graph-based (GNN) encoder, your embeddings will contain much more information on the relationships between different entities in your database.
Very Helpful Article
Thanks, man ๐ฅ
Thanks for sharing insights
My pleasure ๐
I understand that there are three kind of embeddings
Token-based, tree-based, graph-based
This article explainer covers token-based or all 3?
In the end, all embeddings mean the same thing: "they encode some information into a vector"
Depending on your data and the method you use, you can categorize them as token-based, tree-based, graph-based, image-based, etc.
For example, you can encode text data in all the ways you proposed, but depending on the algorithm, you emphasize different aspects. If you use a graph-based (GNN) encoder, your embeddings will contain much more information on the relationships between different entities in your database.
Hope that helps!