topicmodels: An R Package for Fitting Topic Models
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| Authors | Bettina Grün, Kurt Hornik |
| Journal/Conference Name | Journal of Statistical Software |
| Paper Category | Other |
| Paper 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 of publication | 2011 |
| Code Programming Language | R |
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