Learn vector representations of words by continuous bag of words and skip-gram implementations of the 'word2vec' algorithm. The techniques are detailed in the paper "Distributed Representations of Words and Phrases and their Compositionality" by Mikolov et al. (2013), available at <arXiv:1310.4546>.
Version: | 0.3.4 |
Depends: | R (≥ 2.10) |
Imports: | Rcpp (≥ 0.11.5), stats |
LinkingTo: | Rcpp, RcppProgress |
Suggests: | udpipe |
Published: | 2021-07-02 |
Author: | Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), Max Fomichev [ctb, cph] (Code in src/word2vec) |
Maintainer: | Jan Wijffels <jwijffels at bnosac.be> |
License: | Apache License (≥ 2.0) |
URL: | https://github.com/bnosac/word2vec |
NeedsCompilation: | yes |
Materials: | README NEWS |
In views: | NaturalLanguageProcessing |
CRAN checks: | word2vec results |
Reference manual: | word2vec.pdf |
Package source: | word2vec_0.3.4.tar.gz |
Windows binaries: | r-devel: word2vec_0.3.4.zip, r-release: word2vec_0.3.4.zip, r-oldrel: word2vec_0.3.4.zip |
macOS binaries: | r-release (arm64): word2vec_0.3.4.tgz, r-oldrel (arm64): word2vec_0.3.4.tgz, r-release (x86_64): word2vec_0.3.4.tgz, r-oldrel (x86_64): word2vec_0.3.4.tgz |
Old sources: | word2vec archive |
Reverse imports: | GenProSeq, node2vec, wordsalad |
Reverse suggests: | doc2vec, sentencepiece, topicmodels.etm |
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