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Changes in v0.2.0

• Rename word2vec(), doc2vec() and lsa() to textmodel_word2vec(), textmodel_doc2vec() and textmodel_lsa() respectively.
• Simplify the C++ code to make maintenance easier.
• Add normalize to word2vec to disable or enable word vector normalization.
• Add weights() to extract back-propagation weights.
• Make analogy() to convert a formula to named character vector.
• Improve the stability of word2vec() when verbose = TRUE.

Changes in v0.1.0

• Fork https://github.com/bnosac/word2vec and change the package name to wordvector.
• Replace a list of character with quanteda’s tokens object as an input object.
• Recreate word2vec() with new argument names and object structures.
• Create lda() to train word vectors using Latent Semantic Analysis.
• Add similarity() and analogy() functions using proxyC.
• Add data_corpus_news2014 that contain 20,000 news summaries as package data.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.