For top-k product search you could also follow this:
Index all product embeddings through faiss. To get a top match for a given product, take it's embedding & query it with built faiss index, you'll get top-k matches from it. This is way faster than brute force comparision between each pair.
Original_Rip_8182 t1_j5i0ol5 wrote
Reply to Evaluation for similarity search [P] by silverstone1903
For top-k product search you could also follow this: Index all product embeddings through faiss. To get a top match for a given product, take it's embedding & query it with built faiss index, you'll get top-k matches from it. This is way faster than brute force comparision between each pair.
Faiss: https://github.com/facebookresearch/faiss