We show that the word embedding technique word2vec is mathematically equivalent to the gravity law of mobility, making it ideal for learning dense representations from migration data that can be ...

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Word2vec introduced by Mikolov et al. is a word embedding method that is widely used in natural language processing. Despite its success and frequent use, a strong theoretical justification is still ...

Abstract: Word2vec is a widely used algorithm for extracting low-dimensional vector representations of words. State-of-the-art algorithms including those by Mikolov et al. [1] , [2] have been ...

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Abstract: In text, word2vec transforms each word into a fixed-size vector used as the basic component in applications of natural language processing. Given a large collection of unannotated audio, ...

Word2vec is an open source tool developed by a group of Google researchers led by Tomas Mikolov in 2013. It describes several efficient ways to represent words as M-dimensional real vectors, also ...