udpipe universe

The udpipe package is loosely coupled with other NLP packages by the same author. Loosely coupled means that none of the packages have hard dependencies of one another making it easy to install and maintain and allowing you to use only the packages and tools that you want.

Hereby a small list of loosely coupled packages by the same author which contain functions and documentation where the udpipe package is used as a preprocessing step.

BTM: Biterm Topic Modelling: available at https://CRAN.R-project.org/package=BTM
crfsuite: Build named entity recognition models using conditional random fields: https://CRAN.R-project.org/package=crfsuite
nametagger: Build named entity recognition models using markov models: https://CRAN.R-project.org/package=nametagger
torch.ner: Named Entity Recognition using torch
word2vec: Training and applying the word2vec algorithm: https://CRAN.R-project.org/package=word2vec
doc2vec: Building paragraph vector models also known as doc2vec https://CRAN.R-project.org/package=doc2vec
ruimtehol: Text embedding techniques using Starspace: https://CRAN.R-project.org/package=ruimtehol
textrank: Text summarisation and keyword detection using textrank: https://CRAN.R-project.org/package=textrank
brown: Brown word clustering on texts
sentencepiece: Byte Pair Encoding and Unigram tokenisation using sentencepiece: https://CRAN.R-project.org/package=sentencepiece
tokenizers.bpe: Byte Pair Encoding tokenisation using YouTokenToMe: https://CRAN.R-project.org/package=tokenizers.bpe
text.alignment: Find text similarities using Smith-Waterman: https://CRAN.R-project.org/package=text.alignment
textplot: Visualise complex relations in texts: https://CRAN.R-project.org/package=textplot
udpipe: Tokenization, Parts of Speech Tagging, Lemmatization, Dependency Parsing, Keyword detection and NLP processing: https://CRAN.R-project.org/package=udpipe