Topics
Uses global statistics (similar to TF-IDF and latent semantic analysis) such as word co-ocurrence counts, to build text representations (aka word word embeddings).
The driving idea is that the dot product of the word vectors is proportional to the logarithm of the words’ co-occurrence probability
The logarithm term helps with numerical stability during training, when working with very large numbers (like raw co-occurrence counts).