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 |
| 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: | 2020-02-18 |
| 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.tar.gz |
| Windows binaries: | r-devel: text2vec_0.6.zip, r-release: text2vec_0.6.zip, r-oldrel: text2vec_0.6.zip |
| macOS binaries: | r-release: text2vec_0.6.tgz, r-oldrel: text2vec_0.6.tgz |
| Old sources: | text2vec archive |
| Reverse imports: | fdm2id, oolong, textfeatures, textmineR, wactor |
| Reverse suggests: | lime, quanteda, textrecipes |
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