从R中的Document-Term-Matrix过滤行/文档

Question

在RI中使用tm-package创建一个Document-Term-Matrix:

dtm <- DocumentTermMatrix(cor, control = list(dictionary=c("someTerm")))

哪个结果是这样的:

A document-term matrix (291 documents, 1 terms)

Non-/sparse entries: 48/243
Sparsity           : 84%
Maximal term length: 8 
Weighting          : term frequency (tf) 

                   Terms
Docs                someTerm
doc1                       0
doc2                       0
doc3                       7
doc4                       22
doc5                       0

现在我想根据文档中someTerm的出现次数过滤这个Document-Term-Matrix.例如,仅过滤someTerm至少出现一次的文档.即doc3和doc4.

我怎样才能做到这一点？

Answer 1

它与您对常规R矩阵进行子集的方式非常相似.例如,要从示例路透社数据集创建一个文档术语矩阵,其中只有行"似乎"出现多次:

reut21578 <- system.file("texts", "crude", package = "tm")

reuters <- VCorpus(DirSource(reut21578),
    readerControl = list(reader = readReut21578XMLasPlain))

dtm <- DocumentTermMatrix(reuters)
v <- as.vector(dtm[,"would"]>1)
dtm2 <- dtm[v, ]

> inspect(dtm2[, "would"])
A document-term matrix (3 documents, 1 terms)

Non-/sparse entries: 3/0
Sparsity           : 0%
Maximal term length: 5 
Weighting          : term frequency (tf)

     Terms
Docs  would
  246     2
  489     2
  502     2

一个tm文档词矩阵是从包一个简单的三重态基质slam所以slam文档中找出如何操作的DTM帮助.