So maybe what we can do is we can just find everything with another index, like a traditional B-tree index or a bitmap index that's blue, and then evaluate all the vectors.
Making our notation a little more compact again, I'll call this big matrix W down, and similarly call that bias vector B down, and put that back into our diagram.
GraphRag combines vector similarity search with graph traversal, enabling higher accuracy when retrieving information from disparate yet interconnected data sources.