topicmodels: An R Package for Fitting Topic Models

Bettina Grün and Kurt Hornik

Journal of Statistical Software, 2011, vol. 040, issue i13

Abstract: 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.

Date: 2011-05-09
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Citations: View citations in EconPapers (149)

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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:040:i13

DOI: 10.18637/jss.v040.i13

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