inst/paper.md

In bmschmidt/wordVectors: Tools for creating and analyzing vector-space models of texts

title: 'WordVectors: an R environment for training and exploring word2vec modes' tags: - Natural Language Processing - Vector Space Models - word2vec authors: - name: Benjamin M Schmidt orcid: 0000-0002-1142-5720 affiliation: 1 affiliations: - name: Northeastern University index: 1 date: 24 January 2017 bibliography: paper.bib

# Summary

This is an R package for training and exploring word2vec models. It provides wrappers for the reference word2vec implementation released by Google to enable training of vectors from R.[@mikolov_efficient_2013] It also provides a variety of functions enabling exploratory data analysis of word2vec models in an R environment, including 1) functions for reading and writing word2vec's binary form, 2) standard linear algebra functions not bundled in base R (such as cosine similarity) with speed optimizations, and 3) a streamlined syntax for performing vector arithmetic in a vocabulary space.

# References

bmschmidt/wordVectors documentation built on June 2, 2022, 3:53 p.m.