Word2vec
id:
word2vec-181-16518884
title:
Word2vec
text:
Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous words or suggest additional words for a partial sentence. Word2vec was developed by Tomáš Mikolov and colleagues at Google and published in 2013. Word2vec r
brand slug:
wiki
category slug:
encyclopedia
description:
Models used to produce word embeddings
original url:
https://en.wikipedia.org/wiki/Word2vec
date created:
2015-08-14T22:22:48Z
date modified:
2024-09-06T02:20:40Z
main entity:
{"identifier":"Q22673982","url":"https://www.wikidata.org/entity/Q22673982"}
image:
fields total:
13
integrity:
15