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.

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

Author(s): Dmitriy Selivanov*, Lincoln Mullen*

Install package and any missing dependencies by running this line in your R console:

install.packages("text2vec")

Depends R (>= 3.2.0), methods
Imports Matrix(>=1.1), Rcpp(>=0.11), RcppParallel(>=4.3.14), digest(>=0.6.8), foreach(>=1.4.3), data.table(>=1.9.6), magrittr(>=1.5), irlba(>=2.1.2), R6(>=2.1.2)
Suggests stringr(>=1.1.0), testthat, covr, knitr, rmarkdown, glmnet, parallel
Enhances
Linking to Rcpp, RcppParallel, digest
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Package text2vec
Materials
URL http://text2vec.org
Task Views NaturalLanguageProcessing
Version 0.4.0
Published 2016-10-04
License GPL (>= 2) | file LICENSE
BugReports https://github.com/dselivanov/text2vec/issues
SystemRequirements GNU make, C++11
NeedsCompilation yes
Citation
CRAN checks text2vec check results
Package source text2vec_0.4.0.tar.gz