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LSX: Semi-Supervised Algorithm for Document Scaling
A word embeddings-based semi-supervised model for document scaling Watanabe (2020) <doi:10.1080/19312458.2020.1832976>. LSS allows users to analyze large and complex corpora on arbitrary dimensions with seed words exploiting efficiency of word embeddings (SVD, Glove). It can generate word vectors on a users-provided corpus or incorporate a pre-trained word vectors.
Getting started
Browse package contents
Package details |
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| Author | Kohei Watanabe [aut, cre, cph] |
| Maintainer | Kohei Watanabe <watanabe.kohei@gmail.com> |
| License | GPL-3 |
| Version | 1.3.1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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