Model for Semisupervised Text Analysis Based on Word Embeddings

A word embeddings-based semisupervised models for document scaling Watanabe (2017) . LSS allows users to analyze large and complex corpora on arbitrary dimensions with seed words exploiting efficiency of word embeddings (SVD, Glove).


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install.packages("LSX")

0.9.2 by Kohei Watanabe, 9 days ago


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


Authors: Kohei Watanabe [aut, cre, cph]


Documentation:   PDF Manual  


GPL-3 license


Imports digest, Matrix, RSpectra, irlba, rsvd, rsparse, proxyC, grDevices, stats, ggplot2, ggrepel, reshape2, e1071

Depends on quanteda, quanteda.textmodels, methods

Suggests testthat


See at CRAN