ruimtehol: Learn Text 'Embeddings' with 'Starspace'

Wraps the 'StarSpace' library <https://github.com/facebookresearch/StarSpace> allowing users to calculate word, sentence, article, document, webpage, link and entity 'embeddings'. By using the 'embeddings', you can perform text based multi-label classification, find similarities between texts and categories, do collaborative-filtering based recommendation as well as content-based recommendation, find out relations between entities, calculate graph 'embeddings' as well as perform semi-supervised learning and multi-task learning on plain text. The techniques are explained in detail in the paper: 'StarSpace: Embed All The Things!' by Wu et al. (2017), available at <arXiv:1709.03856>.

Version: 0.2.1
Depends: R (≥ 2.10)
Imports: Rcpp (≥ 0.11.5), utils, graphics, stats
LinkingTo: Rcpp, BH
Suggests: udpipe, data.table
Published: 2019-05-31
Author: Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), Facebook, Inc. [cph] (Starspace (BSD licensed))
Maintainer: Jan Wijffels <jwijffels at bnosac.be>
License: MPL-2.0
URL: https://github.com/bnosac/ruimtehol
NeedsCompilation: yes
SystemRequirements: C++11
Materials: README NEWS
CRAN checks: ruimtehol results

Downloads:

Reference manual: ruimtehol.pdf
Vignettes: Neural Text Models with R package ruimtehol
Package source: ruimtehol_0.2.1.tar.gz
Windows binaries: r-devel: ruimtehol_0.2.1.zip, r-release: ruimtehol_0.2.1.zip, r-oldrel: ruimtehol_0.2.1.zip
OS X binaries: r-release: ruimtehol_0.1.2.tgz, r-oldrel: not available
Old sources: ruimtehol archive

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