Often the use case is search. Ex. You have a basic text search engine to find musicians on your site which does some string matching and basic tokenization and so on. But you want to be able to surface similar types of musicians on search too.
In that case you might store vectors representing a user based on some features youve selected, or a word embedding of their common genres/tags.
To actually search this thing, you need something to compare against. You could directly use the word embeddings of the search query. You could also do a search against your existing method, and then use the top results from that as a seed to search your vectors.
Since everything's a vector, you can also ask questions like "what musician is similar to Tom AND Sally" by looking for vectors near T+S. T-S could represent like Tom but not like Sally, etc.
So the answer to what do you store is, what will be your seed to search against?
In that case you might store vectors representing a user based on some features youve selected, or a word embedding of their common genres/tags.
To actually search this thing, you need something to compare against. You could directly use the word embeddings of the search query. You could also do a search against your existing method, and then use the top results from that as a seed to search your vectors.
Since everything's a vector, you can also ask questions like "what musician is similar to Tom AND Sally" by looking for vectors near T+S. T-S could represent like Tom but not like Sally, etc.
So the answer to what do you store is, what will be your seed to search against?