Package: ruimtehol
Type: Package
Title: Learn Text 'Embeddings' with 'Starspace'
Version: 0.3
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Authors@R: c(
    person('Jan', 'Wijffels', role = c('aut', 'cre', 'cph'), email = 'jwijffels@bnosac.be', comment = "R wrapper"), 
    person('BNOSAC', role = 'cph', comment = "R wrapper"), 
    person('Facebook, Inc.', role = 'cph', comment = "Starspace (BSD licensed)"))
Description: 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>.
License: MPL-2.0
URL: https://github.com/bnosac/ruimtehol
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: Rcpp (>= 0.11.5), utils, graphics, stats
Suggests: udpipe, data.table
LinkingTo: Rcpp, BH
RoxygenNote: 7.1.1
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2020-11-27 14:52:15 UTC; Jan
Author: Jan Wijffels [aut, cre, cph] (R wrapper),
  BNOSAC [cph] (R wrapper),
  Facebook, Inc. [cph] (Starspace (BSD licensed))
Repository: CRAN
Date/Publication: 2020-11-29 17:40:02 UTC
Built: R 3.6.2; x86_64-apple-darwin15.6.0; 2020-11-30 16:31:21 UTC; unix
Archs: ruimtehol.so.dSYM
