GloVe (Global Vectors for Word Representation)

GloVe (Global Vectors for Word Representation) is a method for creating word embeddings—mathematical representations of words as vectors. It analyzes how often pairs of words appear together across a large text corpus, capturing the overall statistical relationships between words. By doing so, GloVe encodes semantic similarities; for example, related words like "king" and "queen" will have similar vectors. This approach combines global statistics with local context, enabling computers to understand and process language more effectively. GloVe is widely used in natural language processing tasks such as translation, sentiment analysis, and information retrieval.