Example: stock market
Search results with tag "Em beddings"
CHAPTER Vector Semantics and Embeddings
web.stanford.eduembeddings hypothesis by learning representations of the meaning of words, called embeddings, directly from their distributions in texts. These representations are used in every nat-ural language processing application that makes use of meaning, and the static em-beddings we introduce here underlie the more powerful dynamic or contextualized