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topicmodels: An R Package for Fitting Topic Models

Topic models allow the probabilistic modeling of term frequency occurrences in documents.
The fitted model can be used to estimate the similarity between documents as
well as between a set of specified keywords using an additional layer of latent variables
which are referred to as topics. The R package topicmodels provides basic infrastructure
for fitting topic models based on data structures from the text mining package tm. The
package includes interfaces to two algorithms for fitting topic models: the variational
expectation-maximization algorithm provided by David M. Blei and co-authors and an
algorithm using Gibbs sampling by Xuan-Hieu Phan and co-authors.

Identiferoai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:3987
Date January 2011
CreatorsHornik, Kurt, Grün, Bettina
PublisherAmerican Statistical Association
Source SetsWirtschaftsuniversität Wien
LanguageEnglish
Detected LanguageEnglish
TypeArticle, PeerReviewed
Formatapplication/pdf
Relationhttp://www.jstatsoft.org/v40/i13, http://epub.wu.ac.at/3987/

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