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 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 LICENSE [expanded from: GPL (≥ 2) | file LICENSE] URL: http://text2vec.org NeedsCompilation: yes Materials: README NEWS In views: NaturalLanguageProcessing CRAN checks: text2vec resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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