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: | 0.6.1 |
Depends: | R (≥ 3.6.0), methods |
Imports: | Matrix (≥ 1.1), 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 |
Published: | 2022-04-21 |
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 |
SystemRequirements: | C++11 |
Materials: | README NEWS |
In views: | NaturalLanguageProcessing |
CRAN checks: | text2vec results |
Reference manual: | text2vec.pdf |
Vignettes: |
Advanced topics GloVe Word Embeddings Analyzing Texts with the text2vec Package |
Package source: | text2vec_0.6.1.tar.gz |
Windows binaries: | r-devel: text2vec_0.6.1.zip, r-release: text2vec_0.6.1.zip, r-oldrel: text2vec_0.6.1.zip |
macOS binaries: | r-release (arm64): text2vec_0.6.1.tgz, r-oldrel (arm64): text2vec_0.6.1.tgz, r-release (x86_64): text2vec_0.6.1.tgz, r-oldrel (x86_64): text2vec_0.6.1.tgz |
Old sources: | text2vec archive |
Reverse imports: | conText, fdm2id, regtools, text2map, textfeatures, textmineR, ttgsea, wactor, wordsalad |
Reverse suggests: | lime, oolong, quanteda, sentiment.ai, textrecipes |
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