Question

我有一个600个文本文件的主体，我想从术语Create Table Test1 ( PK1 int not null , PK2 int not null , Primary Key ( PK1, PK2 ) ) Create Table Test2 ( Id int not null Auto_Increment , PK1 int not null , PK2 int not null , Primary Key ( ID ) , Constraint FK_Test2 Foreign Key ( PK1, PK2 ) References Test1( PK1, PK2 ) )之后的每个数字组合中提取它们，并创建mim来找到document term matrix。，它提取了所有想要的术语，但在应用文档术语矩阵时返回了frequencies per file。.我的语料库是一个简单的文本文件语料库，仅包含此代码文本

这是我以这种方式使用时的数据样本；效果很好

library("tm")
library("stringr")
mim<-stringr::str_extract_all(DBcorp,"(mim)[[:blank:]]*[[:digit:]]+")
#extract numbers
mim<-stringr::str_extract_all(mim,"[[:digit:]]+") 
#set the result as list + delete duplicated extracted terms
mim<-unique(unlist(mim[[1]]))
mim
[1] "608106" "606843" "103600" "231550"
class(omim)
[1] "character"
#document term matrix
dtm_mim <- DocumentTermMatrix(DBcorp, control=list(dictionary=mim))

# turn document term matrix into data.frame
df_mim <- data.frame(DOC = dtm_mim$dimnames$Docs, as.matrix(dtm_mim), row.names = NULL , check.names = FALSE)
df_mim

        608106   606843    103600    231550   
1.txt     0        0          0         0
2.txt     0        0          0         0
3.txt     0        0          0         0

但是当我在单独的文本文件中创建文档时，提取失败

docs = c(doc1 = "mim 608106 letters 123 mim 606843 letters 1 letters 123456789 ",
         doc2 = "letters letters 1 mim 231550 123 letters",
         doc3 = "mim 103600 letters 123456")
docs<-Corpus(VectorSource(docs))

Answer 1

请尝试以下代码。如果要在tm语料库上使用函数，则最好使用lapply（或tm_map）。这将仅返回出现在mim中的dtm中的术语。

# note the use of simplify = TRUE. This makes sure you do not get a warning in the line after this one.
mim <- lapply(DBcorp, stringr::str_extract_all, "(mim)[[:blank:]]*[[:digit:]]+", simplify = TRUE)
mim <- lapply(mim, stringr::str_extract_all, "[[:digit:]]+") 
mim <- unique(unlist(mim))

dtm_mim <- DocumentTermMatrix(DBcorp, control = list(dictionary = mim))

df_mim <- data.frame(DOC = dtm_mim$dimnames$Docs, as.matrix(dtm_mim), row.names = NULL , check.names = FALSE)

应用文档术语矩阵时，文档术语矩阵函数返回0

1 个答案: