Package: wordvector 0.1.1

wordvector: Word and Document Vector Models

Create dense vector representation of words and documents using 'quanteda'. Currently implements Word2vec (Mikolov et al., 2013) <doi:10.48550/arXiv.1310.4546> and Latent Semantic Analysis (Deerwester et al., 1990) <doi:10.1002/(SICI)1097-4571(199009)41:6%3C391::AID-ASI1%3E3.0.CO;2-9>.

Authors:Kohei Watanabe [aut, cre, cph], Jan Wijffels [aut], BNOSAC [cph], Max Fomichev [ctb, cph]

wordvector_0.1.1.tar.gz
wordvector_0.1.1.zip(r-4.5)wordvector_0.1.1.zip(r-4.4)wordvector_0.1.1.zip(r-4.3)
wordvector_0.1.1.tgz(r-4.4-x86_64)wordvector_0.1.1.tgz(r-4.4-arm64)wordvector_0.1.1.tgz(r-4.3-x86_64)wordvector_0.1.1.tgz(r-4.3-arm64)
wordvector_0.1.1.tar.gz(r-4.5-noble)wordvector_0.1.1.tar.gz(r-4.4-noble)
wordvector_0.1.1.tgz(r-4.4-emscripten)wordvector_0.1.1.tgz(r-4.3-emscripten)
wordvector.pdf |wordvector.html✨
wordvector/json (API)
NEWS

# Install 'wordvector' in R:
install.packages('wordvector', repos = c('https://koheiw.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/koheiw/wordvector/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

cpp

4.19 score 2 stars 13 scripts 88 downloads 5 exports 23 dependencies

Last updated 6 days agofrom:c8914906cc. Checks:OK: 3 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 19 2024
R-4.5-win-x86_64OKDec 19 2024
R-4.5-linux-x86_64OKDec 19 2024
R-4.4-win-x86_64NOTEDec 19 2024
R-4.4-mac-x86_64NOTEDec 19 2024
R-4.4-mac-aarch64NOTEDec 19 2024
R-4.3-win-x86_64NOTEDec 19 2024
R-4.3-mac-x86_64NOTEDec 19 2024
R-4.3-mac-aarch64NOTEDec 19 2024

Exports:analogydoc2veclsasimilarityword2vec

Dependencies:clifastmatchglueirlbaISOcodesjsonlitelatticelifecyclemagrittrMatrixproxyCquantedaRcppRcppArmadilloRcppEigenrlangRSpectrarsvdSnowballCstopwordsstringixml2yaml