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.
Package details |
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Maintainer | |
License | GPL-3 |
Version | 1.4.2 |
URL | https://koheiw.github.io/LSX/ |
Package repository | View on GitHub |
Installation |
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