Group of related models that are used to produce word embeddings
Also known as word2vec
23 statements · 13% with external sources · numbers in brackets are citations
8 identifiers linking Word2vec across the web's reference databases
From Wikipedia, the free encyclopedia · Read full article · Text CC BY-SA 4.0
In natural language processing, Word2Vec is a technique for obtaining vector representations of words as word embeddings. These vectors capture information about the meaning of a word based on its surrounding words in a piece of text, following the principles of distributional semantics. Once trained, the model can be used to find words with similar meanings or usage, while its embeddings can serve as inputs to systems for search and classification.