GloVe

GloVe is an important word embedding method that combines local context-window learning with global statistical information. Derived from a word-word co-occurrence matrix, it aims to produce more stable semantic vectors. It became a strong and widely used representation approach during the classical NLP era. It remains historically important for understanding different ways of modeling distributional semantics.