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Word Embedding - Why is word embedding better?
Answer
To approximate the meanings of words in a two-dimensional flat environment, word embeddings work well. Models like WordNet's graph embeddings, which are hand-built, are significantly more difficult to train than these. A word embedding with fifty values, for example, may stand in for fifty distinct features.
