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Word Embeddings: A Survey

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arxiv 1901.09069 v2 pith:DVRMNNHV submitted 2019-01-25 cs.CL cs.LGstat.ML

classification cs.CLcs.LGstat.ML
keywords embeddingsrepresentationswordadditionbeenbuildingcalledcommonly
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This work lists and describes the main recent strategies for building fixed-length, dense and distributed representations for words, based on the distributional hypothesis. These representations are now commonly called word embeddings and, in addition to encoding surprisingly good syntactic and semantic information, have been proven useful as extra features in many downstream NLP tasks.

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Cited by 4 Pith papers

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