Vector embeddings will not solve search: a decades-old term-frequency algorithm still beats most of them at ranking.

Co-founder and CEO of Perplexity, an AI answer engine

There is an algorithm called BM25 precisely for this, which is a more sophisticated version of TF-IDF. TF-IDF is term frequency times inverse document frequency, a very old-school information retrieval system that just works actually really well even today. And BM25 is a more sophisticated version of that, that is still beating most embeddings on ranking.