topicmodels: Topic Models

Provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.

Version: 0.2-12
Depends: R (≥ 2.15.0)
Imports: stats4, methods, modeltools, slam, tm (≥ 0.6)
Suggests: lasso2, lattice, lda, OAIHarvester, SnowballC, corpus.JSS.papers
Published: 2021-01-29
Author: Bettina Grün ORCID iD [aut, cre], Kurt Hornik ORCID iD [aut], David M Blei [ctb, cph] (VEM estimation of LDA and CTM), John D Lafferty [ctb, cph] (VEM estimation of CTM), Xuan-Hieu Phan [ctb, cph] (MCMC estimation of LDA), Makoto Matsumoto [ctb, cph] (Mersenne Twister RNG), Takuji Nishimura [ctb, cph] (Mersenne Twister RNG), Shawn Cokus [ctb] (Mersenne Twister RNG)
Maintainer: Bettina Grün <Bettina.Gruen at>
License: GPL-2
NeedsCompilation: yes
SystemRequirements: GNU Scientific Library version >= 1.8, C++11
Citation: topicmodels citation info
Materials: NEWS
In views: NaturalLanguageProcessing
CRAN checks: topicmodels results


Reference manual: topicmodels.pdf
Vignettes: topicmodels: An R Package for Fitting Topic Models
Package source: topicmodels_0.2-12.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: topicmodels_0.2-12.tgz, r-oldrel: topicmodels_0.2-12.tgz
Old sources: topicmodels archive

Reverse dependencies:

Reverse depends: BullsEyeR
Reverse imports: cellTree, LDAShiny, LDATS, ldatuning, MoMPCA, musicatk, oRus, revtools, topicdoc
Reverse suggests: corpustools, GermaParl, LDAvis, oolong, quanteda, seededlda, textmineR, TextMiningGUI, tidytext, udpipe


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