Miklov et al. introduced the world to the power of word vectors by showing two main methods: Skip–Gram and Continuous Bag of Words (CBOW). Soon after, two more popular word embedding methods built on these methods were discovered. In this post, we’ll talk about GloVe and fastText, which are extremely popular word vector models in the NLP world.
Global Vectors (GloVe)
Pennington et al. argue that the online scanning approach used by word2vec is suboptimal since it does not fully exploit the global statistical information regarding word co-occurrences.