首页 文章

R词 Cloud - 无法删除英语停用词

提问于
浏览 次
0

我尝试在构建文字 Cloud 之前从文本中删除英语停用词，但它不起作用 . 我读了好几篇文章并尝试了没有运气的建议 . 任何帮助将不胜感激 .

library(tm)
library(wordcloud)
library(RColorBrewer)
library(SnowballC)

textdata <- c(A secur breach expos privat inform of student loan borrow from Aug. 20-22 dure a comput softwar upgrade. User of the DOE Direct Loan Web site were abl to view inform other than their own if they use certain option when access the program web pages. SSNs were among the data element expos online.  Softwar compani Affiliat Comput Servic (ACS) creat the technolog for the Direct Loan Servic featur on the DoE site. )


#Create corpus and clean data
txt <- Corpus(VectorSource(textdata))
txtCorpus <- tm_map(txt, removePunctuation)
txtCorpus <- tm_map(txt, removeNumbers)
txtCorpus <- tm_map(txt, content_transformer(tolower))
txtCorpus <- tm_map(txtCorpus, removeWords, stopwords("english"))
txtCorpus <- tm_map(txt, stripWhitespace); #inspect(docs[1])
txtCorpus <- tm_map(txt, stemDocument)

#Creat tdm
tdm <- TermDocumentMatrix(txtCorpus)
m <- as.matrix(tdm)
v <- sort(rowSums(m),decreasing=TRUE)
d <- data.frame(word = names(v),freq=v, stringsAsFactors = FALSE)
head(d, 10)

产量

word    freq

the     the     8469        
and     and     5790        
inform  inform  2629        
was     was     2487        
secur   secur   2249        
were    were    1901        
social  social  1890
r word-count stop-words

1 回答

  • 0

    修复你的语料库清理：

    library(tm)
library(wordcloud)
library(RColorBrewer)
library(SnowballC)
textdata <- c("A secur breach expos privat inform of student loan borrow from Aug. 20-22 dure a comput softwar upgrade. User of the DOE Direct Loan Web site were abl to view inform other than their own if they use certain option when access the program web pages. SSNs were among the data element expos online.  Softwar compani Affiliat Comput Servic (ACS) creat the technolog for the Direct Loan Servic featur on the DoE site. ")
corp <- Corpus(VectorSource(textdata))
corp <- tm_map(corp, removePunctuation)
corp <- tm_map(corp, removeNumbers)
corp <- tm_map(corp, content_transformer(tolower))
corp <- tm_map(corp, removeWords, stopwords("english"))
corp <- tm_map(corp, stripWhitespace); #inspect(docs[1])
corp <- tm_map(corp, stemDocument)

tdm <- TermDocumentMatrix(corp)
m <- as.matrix(tdm)
v <- sort(rowSums(m),decreasing=TRUE)
d <- data.frame(word = names(v),freq=v, stringsAsFactors = FALSE)
head(d, 10)
#            word freq
# loan       loan    3
# comput   comput    2
# direct   direct    2
# doe         doe    2
# expo       expo    2
# inform   inform    2
# servic   servic    2
# site       site    2
# softwar softwar    2
# web         web    2
    回复于

相关问题