will not be very accurate and you can also have noise from very frequent words like like like you know words like a or D or articles and these are going to be very frequently present so you have to use some heuristics like inverse document frequency to make sure that they don't corrupt your bearings and it's however all of this sounds like a very hockey engineered pipeline and it's not particularly efficient and it's not going to scale well with like larger larger the vocabularies or like larger data sets it's it's very hard to scale