Parse a character vector of documents into into both sentences and a clean vector of tokens. The resulting output includes IDs for document and sentence for use in other lexRank functions.
sentenceTokenParse(text, docId = "create", removePunc = TRUE,
removeNum = TRUE, toLower = TRUE, stemWords = TRUE,
rmStopWords = TRUE)A character vector of documents to be parsed into sentences and tokenized.
A character vector of document Ids the same length as text. If docId=="create" document Ids will be created.
TRUE or FALSE indicating whether or not to remove punctuation from text while tokenizing. If TRUE, punctuation will be removed. Defaults to TRUE.
TRUE or FALSE indicating whether or not to remove numbers from text while tokenizing. If TRUE, numbers will be removed. Defaults to TRUE.
TRUE or FALSE indicating whether or not to coerce all of text to lowercase while tokenizing. If TRUE, text will be coerced to lowercase. Defaults to TRUE.
TRUE or FALSE indicating whether or not to stem resulting tokens. If TRUE, the outputted tokens will be tokenized using SnowballC::wordStem(). Defaults to TRUE.
TRUE, FALSE, or character vector of stopwords to remove from tokens. If TRUE, words in lexRankr::smart_stopwords will be removed prior to stemming. If FALSE, no stopword removal will occur. If a character vector is passed, this vector will be used as the list of stopwords to be removed. Defaults to TRUE.
A list of dataframes. The first element of the list returned is the sentences dataframe; this dataframe has columns docId, sentenceId, & sentence (the actual text of the sentence). The second element of the list returned is the tokens dataframe; this dataframe has columns docId, sentenceId, & token (the actual text of the token).
# NOT RUN {
sentenceTokenParse(c("Bill is trying to earn a Ph.D.", "You have to have a 5.0 GPA."),
docId=c("d1","d2"))
# }
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