Modern Text Mining Framework for R [R package text2vec version 0.6.6]

text2vec: Modern Text Mining Framework for R

Fast and memory-friendly tools for text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), similarities. This package provides a source-agnostic streaming API, which allows researchers to perform analysis of collections of documents which are larger than available RAM. All core functions are parallelized to benefit from multicore machines.

Version: 0.6.6

Depends: R (≥ 3.6.0), methods

Imports: Matrix (≥ 1.5-2), Rcpp (≥ 1.0.3), R6 (≥ 2.3.0), data.table (≥ 1.9.6), rsparse (≥ 0.3.3.4), stringi (≥ 1.1.5), mlapi (≥ 0.1.0), lgr (≥ 0.2), digest (≥ 0.6.8)

LinkingTo: Rcpp, digest (≥ 0.6.8)

Suggests: magrittr, udpipe (≥ 0.6), glmnet, testthat, covr, knitr, rmarkdown, proxy, LDAvis

Published: 2025年12月01日

DOI: 10.32614/CRAN.package.text2vec

Author: Dmitriy Selivanov [aut, cre, cph], Manuel Bickel [aut, cph] (Coherence measures for topic models), Qing Wang [aut, cph] (Author of the WaprLDA C++ code)

Maintainer: Dmitriy Selivanov <selivanov.dmitriy at gmail.com>

BugReports: https://github.com/dselivanov/text2vec/issues

License: GPL-2 | GPL-3 | file LICENSE [expanded from: GPL (≥ 2) | file LICENSE]

URL: http://text2vec.org

NeedsCompilation: yes

Materials: README, NEWS

In views: NaturalLanguageProcessing

CRAN checks: text2vec results