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 🥂
Thanks for sharing insights
My pleasure 😇
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!