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Analyzed from 64 words in the discussion.

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#word#query#document#curious#ranking#holds#messy#product#text#versus

Discussion (2 Comments)Read Original on HackerNews

torutofuβ€’about 9 hours ago
Curious how the ranking holds up on messy product text versus something like ParadeDB.
dukepikiβ€’about 3 hours ago
BM25 is pretty similar everywhere: if a word in your query appears a lot in a document, the score for that document (for that one query) goes up, especially if that word isn't in very many other documents.

There are a couple of tuning parameters, and the notion of what a "word" is varies based on the tokenizer and stemming you use.

So it won't be exactly the same, but it's likely to be close.