Re:Deep Learning at x.ai
by jknz on Friday March 25, 2016 @11:25AM
(#11360569)
One could argue that Word embeddings are also dimensionality-reduction techniques: Words live in an infinite dimensional space, and the embeddings is a finite-dimensional projection of this infinte dimensional space.
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I think of word vectors in the opposite light. Words stored in a dictionary have 1-dimension (their index), making comparisons more or less random. Word vectors augment the information you have about a word by continually examining the context that the word appears in a corpus of text.