matrix and you would get a user embedding in an item embedding and you just cluster or similar users in similar items and you will use it to build a recommender system so similarly you can think of building a term frequency resistant frequency matrix here in a low peak and constructing a sweetie and get word embeddings so that's that's precisely what's being done here and you can get these U and V vectors so so what is the problem with the SVD approach this video prods the first one sparsity right so obviously there may be very