如何將具有單個列的R數據幀轉換為tm的語料庫，以便將每一行作為文檔？

Question

我想使用tm包的findAssocs命令，但只有在語料庫中有多個文檔時它才有效。 相反，我有一個單列數據框，其中每一行包含來自Tweet的文本。 是否可以將其轉換為將每行作為新文檔的語料庫？

VCorpus (documents: 1, metadata (corpus/indexed): 0/0)
TermDocumentMatrix (terms: 71, documents: 1)

我有10行數據，我希望它被轉換為

VCorpus (documents: 10, metadata (corpus/indexed): 0/0)
TermDocumentMatrix (terms: 71, documents: 10)

Answer 1

我建議你在繼續之前先閱讀tm -vignette。 回答下面的具體問題。

創建示例數據：

txt <- strsplit("I wanted to use the findAssocs of the tm package. but it works only when there are more than one documents in the corpus. I have a data frame table which has one column and each row has a tweet text. Is it possible to convert the into a corpus which takes each row as a new document?", split=" ")[[1]]
data <- data.frame(text=txt, stringsAsFactors=FALSE)
data[1:5, ]

將您的數據導入“源”，將“源”導入“語料庫”，然后從“語料庫”中創建TDM：

library(tm)
tdm <- TermDocumentMatrix(Corpus(DataframeSource(data)))

show(tdm)
#A term-document matrix (35 terms, 58 documents)
#
#Non-/sparse entries: 43/1987
#Sparsity           : 98%
#Maximal term length: 10 
#Weighting          : term frequency (tf)

str(tdm)
#List of 6
# $ i       : int [1:43] 32 31 28 12 28 21 3 35 20 33 ...
# $ j       : int [1:43] 2 4 5 6 8 10 11 13 14 15 ...
# $ v       : num [1:43] 1 1 1 1 1 1 1 1 1 1 ...
# $ nrow    : int 35
# $ ncol    : int 58
# $ dimnames:List of 2
#  ..$ Terms: chr [1:35] "and" "are" "but" "column" ...
#  ..$ Docs : chr [1:58] "1" "2" "3" "4" ...
# - attr(*, "class")= chr [1:2] "TermDocumentMatrix" "simple_triplet_matrix"
# - attr(*, "Weighting")= chr [1:2] "term frequency" "tf"