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>.
|Author||Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), Facebook, Inc. [cph] (Starspace (BSD licensed))|
|Maintainer||Jan Wijffels <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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