text2vec: Modern Text Mining Framework for R (original) (raw)
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: | 0.6.4 | ||
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| 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 | ||
| Published: | 2023-11-09 | ||
| 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 [expanded from: GPL (≥ 2) | file LICENSE] |
| URL: | http://text2vec.org | ||
| NeedsCompilation: | yes | ||
| Materials: | README NEWS | ||
| In views: | NaturalLanguageProcessing | ||
| CRAN checks: | text2vec results |
Documentation:
Downloads:
Reverse dependencies:
| Reverse imports: | conText, kgraph, NUSS, occupationMeasurement, PsychWordVec, regtools, text2map, textmineR, ttgsea, wactor, wordsalad |
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| Reverse suggests: | fdm2id, lime, oolong, opticskxi, polyglotr, sentiment.ai, textrecipes |
| Reverse enhances: | quanteda |
Linking:
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