seededlda: Seeded Sequential LDA for Topic Modeling

Seeded Sequential LDA can classify sentences of texts into pre-define topics with a small number of seed words (Watanabe & Baturo, 2023) <doi:10.1177/08944393231178605>. Implements Seeded LDA (Lu et al., 2010) <doi:10.1109/ICDMW.2011.125> and Sequential LDA (Du et al., 2012) <doi:10.1007/s10115-011-0425-1> with the distributed LDA algorithm (Newman, et al., 2009) for parallel computing.

Version: 1.3.0
Depends: R (≥ 3.5.0), quanteda (≥ 4.0.0), methods, proxyC (≥ 0.3.1)
Imports: Matrix
LinkingTo: Rcpp, RcppArmadillo (≥ 0.7.600.1.0), quanteda, testthat
Suggests: spelling, testthat, topicmodels, keyATM
Published: 2024-06-19
DOI: 10.32614/CRAN.package.seededlda
Author: Kohei Watanabe [aut, cre, cph], Phan Xuan-Hieu [aut, cph] (GibbsLDA++)
Maintainer: Kohei Watanabe <watanabe.kohei at>
License: GPL-3
NeedsCompilation: yes
Language: en-US
Citation: seededlda citation info
Materials: NEWS
CRAN checks: seededlda results


Reference manual: seededlda.pdf


Package source: seededlda_1.3.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): seededlda_1.3.0.tgz, r-oldrel (arm64): seededlda_1.3.0.tgz, r-release (x86_64): seededlda_1.3.0.tgz, r-oldrel (x86_64): seededlda_1.3.0.tgz
Old sources: seededlda archive

Reverse dependencies:

Reverse imports: oolong
Reverse suggests: sentopics


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