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 .


Reference manual

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0.1.2 by Jan Wijffels, 19 days ago


Browse source code at https://github.com/cran/ruimtehol

Authors: Jan Wijffels [aut, cre, cph] (R wrapper) , BNOSAC [cph] (R wrapper) , Facebook , Inc. [cph] (Starspace (BSD licensed))

Documentation:   PDF Manual  

MPL-2.0 license

Imports Rcpp, utils, graphics, stats

Suggests udpipe, data.table

Linking to Rcpp, BH

System requirements: C++11, GNU make

See at CRAN