text2vec: Fast and Modern Text Mining Framework - Vectorization and Word Embeddings

Very fast and memory-friendly tools for text vectorization and learning word embeddings (GloVe). Also package provides source-agnostic streaming API, which allows to perform analysis of collections of documents, which are much larger the available RAM.

Version: 0.2.0
Depends: R (≥ 3.2.0), methods
Imports: Matrix (≥ 1.1), Rcpp (≥ 0.11), RcppParallel (≥ 4.3.14), digest (≥ 0.6.8), magrittr (≥ 1.5), stringr (≥ 1.0.0), iterators (≥ 1.0.8), readr (≥ 0.2.2)
LinkingTo: Rcpp, RcppParallel, digest
Suggests: testthat, knitr, rmarkdown, glmnet
Published: 2016-01-10
Author: Dmitriy Selivanov [aut, cre]
Maintainer: Dmitriy Selivanov <selivanov.dmitriy at gmail.com>
BugReports: https://github.com/dselivanov/text2vec/issues
License: MIT + file LICENSE
URL: https://github.com/dselivanov/text2vec
NeedsCompilation: yes
SystemRequirements: GNU make, C++11
Materials: README
CRAN checks: text2vec results


Reference manual: text2vec.pdf
Vignettes: GloVe word embeddings.
Analyzing texts with text2vec package.
Package source: text2vec_0.2.0.tar.gz
Windows binaries: r-devel: text2vec_0.2.0.zip, r-release: text2vec_0.2.0.zip, r-oldrel: not available
OS X Snow Leopard binaries: r-release: not available, r-oldrel: not available
OS X Mavericks binaries: r-release: text2vec_0.2.0.tgz