A language model is a probability distribution that describes how frequent an occurrence of a particular sequence of words is. This modeling is nowadays used in the various applications of Natural Language Processing, such as machine translation, speech recognition, part-of-speech tagging, parsing and others.
The Sketch Engine team prepared word embeddings, language models trained using fastText from the multi-billion-word corpora available in Sketch Engine. In a nutshell, the embedding means a word vector which describes word relations described by numbers (lengths) and directions.
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Practical examples of using word embeddings include creating a thesaurus or word analogy (finding similar relations on the same principle, e.g. king – man, queen – woman). See the example from our embeddings viewer for the query king -man +woman (you will get queen, princess, …).