<sod>'''Word embedding''' is the collective name for a set of [[language model]]ing and [[feature learning]] techniques in [[natural language processing]] (NLP) where words or phrases from the vocabulary are mapped to vectors of [[real numbers]] in a low-dimensional space relative to the vocabulary size ("continuous space").<eod>
<sod>'''Word embedding''' is the collective name for a set of [[language model]]ing and [[feature learning]] techniques in [[natural language processing]] (NLP) where words or phrases from the vocabulary are mapped to vectors of [[real numbers]]. Conceptually it involves a mathematical [[embedding]] from a space with one dimension per word to a continuous [[vector space]] with much lower dimension.<eod>