cleanNLP v3.0.3

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A Tidy Data Model for Natural Language Processing

Provides a set of fast tools for converting a textual corpus into a set of normalized tables. Users may make use of the 'udpipe' back end with no external dependencies, or two Python back ends with 'spaCy' <https://spacy.io> or 'CoreNLP' <https://stanfordnlp.github.io/CoreNLP/>. Exposed annotation tasks include tokenization, part of speech tagging, named entity recognition, and dependency parsing.

Functions in cleanNLP

Name Description
cnlp_utils_tfidf Construct the TF-IDF Matrix from Annotation or Data Frame
cnlp_init_spacy Interface for initializing the spacy backend
cnlp_download_corenlp Download model files needed for coreNLP
cnlp_init_udpipe Interface for initializing the udpipe backend
cnlp_utils_pca Compute Principal Components and store as a Data Frame
cnlp_init_corenlp Interface for initializing the coreNLP backend
cnlp_download_spacy Download model files needed for spacy
cnlp_init_stringi Interface for initializing the standard R backend
cleanNLP-package cleanNLP: A Tidy Data Model for Natural Language Processing
un Universal Declaration of Human Rights
word_frequency Most frequent English words
cnlp_annotate Run the annotation pipeline on a set of documents
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Vignettes of cleanNLP

Name
img/fig1.png
img/fig2.png
img/fig3.png
img/fig4.png
state-of-union.Rmd
wikipedia.Rmd
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Details

Type Package
SystemRequirements Python (>= 3.7.0)
License LGPL-2
URL https://statsmaths.github.io/cleanNLP/
BugReports https://github.com/statsmaths/cleanNLP/issues
LazyData true
VignetteBuilder knitr
RoxygenNote 7.1.1
NeedsCompilation no
Packaged 2020-10-12 21:38:15 UTC; admin
Repository CRAN
Date/Publication 2020-10-13 04:10:02 UTC

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