我正在尝试创建一个 DocumentTermMatrix，同时保留所有特殊字符

Question

尝试在不删除任何特殊字符的情况下使用 R 进行一些文本挖掘。例如下面的 "LKC" 和 "LKC_" 应该是不同的词。相反，它删除了 _ 并使其成为同一个词。我怎样才能做到这一点？

library(tm)
special = c("OLAC_ LA LAC LAC_ LAC_E AC AC_ AC_E AC_ET",
                      ")LK )LKC )LKC- LK LKC LKC-",
                      "LAC_ LAC_E LKC LKC-")

bagOfWords <- Corpus(VectorSource(special))


mydocsDTM <- DocumentTermMatrix(bagOfWords, control = list(removePunctuation = FALSE,                     
preserve_intra_word_contractions = FALSE,         
preserve_intra_word_dashes = FALSE,
removeNumbers = FALSE,
stopwords = FALSE,
stemming = FALSE
))

  inspect(mydocsDTM)

Answer 1

使用 quanteda 包轻松完成，之后您可以转换为 DocumentTermMatrix，或者继续使用 quanteda.

library("quanteda")
qdfm <- dfm(special, tolower = FALSE, what = "fasterword")
qdfm
# Document-feature matrix of: 3 documents, 15 features (57.8% sparse).
# 3 x 15 sparse Matrix of class "dfm"
#        features
# docs    OLAC_ LA LAC LAC_ LAC_E AC AC_ AC_E AC_ET )LK )LKC )LKC- LK LKC LKC-
#   text1     1  1   1    1     1  1   1    1     1   0    0     0  0   0    0
#   text2     0  0   0    0     0  0   0    0     0   1    1     1  1   1    1
#   text3     0  0   0    1     1  0   0    0     0   0    0     0  0   1    1

convert(qdfm, to = "tm")
# <<DocumentTermMatrix (documents: 3, terms: 15)>>
# Non-/sparse entries: 19/26
# Sparsity           : 58%
# Maximal term length: 5
# Weighting          : term frequency (tf)

我正在尝试创建一个 DocumentTermMatrix，同时保留所有特殊字符

I am trying to create a DocumentTermMatrix while keeping all special characters

r

special-characters

tm

term-document-matrix