I am a bit confused about the interpretation of word2vec output vectors! If I want to predict the most probable word that will appear after a specific word(w1), can I use the most nearest word to w1? I mean, a word having the shortest distance from w1 can be interpreted as the next word with the highest probability?
How word2vec output vectors are used to compute the similarities?
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This is called language modeling
no: the nearest word to w1 is the most semantically close word to w1.