Changes in version 0.5.2 (2019-03-17)                  

  - fix damping bug where damping parameter wasn't passed to
    igraph::pagerank

                        Changes in version 0.5.1                        

  - changed smart_stopwords to be internal data so that package doesnt
    need to be explicitly loaded with library to be able to parse

                 Changes in version 0.5.0 (2017-12-13)                  

  - bug fix in sentence parsing for parsing exclamatory sentences
  - converted idf calculation from idf(d, t) = log( n / df(d, t) ) to
    idf(d, t) = log( n / df(d, t) ) + 1 to avoid zeroing out common word
    tfidf values
  - removed dplyr, tidyr, stringr, magrittr, & tm as dependencies
  - created option to bypass assumption that each row/vector-element are
    different documents in lexRank and unnest_sentences
  - various bug fixes in token & sentence parsing

                 Changes in version 0.4.1 (2017-05-10)                  

  - added bug report url:
    (https://github.com/AdamSpannbauer/lexRankr/issues/)
  - formatting updates to README.md

                 Changes in version 0.4.0 (2017-03-02)                  

  - added functions unnest_sentences and unnest_sentences_ to parse
    sentences in a dataframe following tidy data principles
  - added functions bind_lexrank and bind_lexrank_ to calculate lexrank
    scores for sentences in a dataframe following tidy data principles
    (unnest_sentences & bind_lexrank can be used on a df in a magrittr
    pipeline)
  - added vignette for using lexrank to analyze tweets

                 Changes in version 0.3.0 (2016-10-25)                  

  - sentence similarity from sentenceSimil now calculated using Rcpp.
    Improves speed by ~25%-30% over old implementation using proxy
    package

                 Changes in version 0.2.0 (2016-09-22)                  

  - Added logic to avoid naming conflicts in proxy::pr_DB in
    sentenceSimil (#1, @AdamSpannbauer)

  - Added check and error for cases where no sentences above threshold
    in lexRankFromSimil (#2, @AdamSpannbauer)

  - tokenize now has stricter punctuation removal. Removes all
    non-alphnumeric characters as opposed to removing [:punct:]