3 SVD Based Methods
For this class of methods to find word embeddings (otherwise known as word vectors), we first loop over a massive data set and accumulate word co-occurrence counts in some form of a matrix X and then perform Singular Value Decomposition on X to get a USV^T decomposition. We then use the rows of U as the word embeddings for all words in our dictionary. Let us discuss a few choices of X.
Above is the excerpt from the standford univ cs224n lecture 1 notes.
Above USV refer to what? There's no prior explanation about it so I ask here.