Not precisely, but if you had 50 documents in that 1000-dimensional embedding and you reduced the dimensions to three and still got at least the exact same nearest neighbor ordering then it would at least still function, right?
I guess the problem is taking a new document (like a search term) in the higher dimensional embedding and reducing it to three dimensions for searching in that reduced space and expecting that to also maintain the same nearest neighbor ordering.
I guess the problem is taking a new document (like a search term) in the higher dimensional embedding and reducing it to three dimensions for searching in that reduced space and expecting that to also maintain the same nearest neighbor ordering.