SPLADE for Sparse Vector Search Explained

Google, Netflix, Amazon, and many more big tech companies all have one thing in common. They power their search and recommendation systems with “vector search”.

Before modern vector search, we had the “traditional” bag of words (BOW) methods. That is, we take a set of " documents" to be retrieved (like web pages on Google). Each document is transformed into a set (bag) of words, and use this to populate a sparse “frequency vector”. Popular algorithms for this include TF-IDF and BM25.

This is a companion discussion topic for the original entry at https://www.pinecone.io/learn/splade/