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seededlda (version 1.1.0)

Seeded Sequential LDA for Topic Modeling

Description

Seeded Sequential LDA can classify sentences of texts into pre-define topics with a small number of seed words (Watanabe & Baturo, 2023) . Implements Seeded LDA (Lu et al., 2010) and Sequential LDA (Du et al., 2012) with the distributed LDA algorithm (Newman, et al., 2009) for parallel computing.

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Install

install.packages('seededlda')

Monthly Downloads

649

Version

1.1.0

License

GPL-3

Issues

Pull Requests

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Repository

https://github.com/koheiw/seededlda

Homepage

https://koheiw.github.io/seededlda/

Maintainer

Kohei Watanabe

Last Published

July 1st, 2023

Functions in seededlda (1.1.0)

textmodel_seqlda

Sequential Latent Dirichlet allocation

textmodel_seededlda

Semisupervised Latent Dirichlet allocation

Extract most likely topics

Optimize the number of topics

data_corpus_moviereviews

Movie reviews from Pang and Lee (2004)

Compute the sizes of topics

print.textmodel_lda

Print method for a LDA model

Extract most likely terms

Unsupervised Latent Dirichlet allocation