Ropensci Tokenizers Versions Save

• Add citation information to JOSS paper.

Features

• Add the tokenize_ptb() function for Penn Treebank tokenizations (@jrnold) (#12).
• Add a function chunk_text() to split long documents into pieces (#30).
• New functions to count words, characters, and sentences without tokenization (#36).
• New function tokenize_tweets() preserves usernames, hashtags, and URLS (@kbenoit) (#44).
• The stopwords() function has been removed in favor of using the stopwords package (#46).
• The package now complies with the basic recommendations of the Text Interchange Format. All tokenization functions are now methods. This enables them to take corpus inputs as either TIF-compliant named character vectors, named lists, or data frames. All outputs are still named lists of tokens, but these can be easily coerced to data frames of tokens using the tif package. (#49)
• Add a new vignette "The Text Interchange Formats and the tokenizers Package" (#49).

Bug fixes and performance improvements

• tokenize_skip_ngrams has been improved to generate unigrams and bigrams, according to the skip definition (#24).
• C++98 has replaced the C++11 code used for n-gram generation, widening the range of compilers tokenizers supports (@ironholds) (#26).
• tokenize_skip_ngrams now supports stopwords (#31).
• If tokenisers fail to generate tokens for a particular entry, they return NA consistently (#33).
• Keyboard interrupt checks have been added to Rcpp-backed functions to enable users to terminate them before completion (#37).
• tokenize_words() gains arguments to preserve or strip punctuation and numbers (#48).
• tokenize_skip_ngrams() and tokenize_ngrams() to return properly marked UTF8 strings on Windows (@patperry) (#58).

• Add the tokenize_character_shingles() tokenizer.
• Improvements to documentation.

• Initial release with tokenizers for characters, words, word stems, sentences paragraphs, n-grams, skip n-grams, lines, and regular expressions.

• Fix failing test in non-UTF-8 locales.

• Add stopwords for several languages.
• New stopword options to tokenize_words() and tokenize_word_stems().

• Add vignette.
• Improvements to n-gram tokenizers.