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April 29-30, 2017
100 Speakers - 2 Days

Word2vec and friends

Bruno Gonçalves, New York University

Word embeddings have received a lot of attention since some Googlers published word2vec in 2013 and showed that the embeddings that the neural network learned by "reading" a large corpus of text preserved semantic relations between words. As a result, this type of embedding started being studied in more detail and applied to more serious NLP and IR tasks such as summarization, query expansion, etc...

In this talk Bruno is covering the implementation and mathematical details underlying tools like word2vec and some of the applications word embeddings have found in various areas. An overview of the emerging field of "<anything>2vec" (phrase2vec, doc2vec, dna2vec, node2vec, etc...) methods that use variations of the word2vec neural network architecture will also be presented.