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text2vec: Modern Text Mining Framework for R
Fast and memory-friendly tools for text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), similarities. This package provides a source-agnostic streaming API, which allows researchers to perform analysis of collections of documents which are larger than available RAM. All core functions are parallelized to benefit from multicore machines.
Getting started
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Package details |
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| Author | Dmitriy Selivanov [aut, cre, cph], Manuel Bickel [aut, cph] (Coherence measures for topic models), Qing Wang [aut, cph] (Author of the WaprLDA C++ code) |
| Maintainer | Dmitriy Selivanov <selivanov.dmitriy@gmail.com> |
| License | GPL (>= 2) | file LICENSE |
| Version | 0.6.4 |
| URL | http://text2vec.org |
| Package repository | View on CRAN |
| Installation |
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