我尝试在构建文字云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)
输出
word freq
the the 8469
and and 5790
inform inform 2629
was was 2487
secur secur 2249
were were 1901
social social 1890
答案 0 :(得分:0)
修复您的语料库清理:
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