我的test.csv文件内容如下（无表头）：
very good, very bad, you are greatvery bad, good restaurent, nice place to visit我想将我的语料库用,分隔开，这样我的最终DocumentTermMatrix会变成这样：
terms docs very good very bad you are great good restaurent nice place to visit doc1 tf-idf tf-idf tf-idf 0 0 doc2 0 tf-idf 0 tf-idf tf-idf如果我不从csv文件加载documents，我可以正确生成上面的DTM，如下所示：
library(tm)docs <- c(D1 = "very good, very bad, you are great", D2 = "very bad, good restaurent, nice place to visit")dd <- Corpus(VectorSource(docs))dd <- tm_map(dd, function(x) { PlainTextDocument( gsub("\\s+","~",strsplit(x,",\\s*")[[1]]), id=ID(x) )})inspect(dd)# A corpus with 2 text documents# # The metadata consists of 2 tag-value pairs and a data frame# Available tags are:# create_date creator # Available variables in the data frame are:# MetaID # $D1# very~good# very~bad# you~are~great# # $D2# very~bad# good~restaurent# nice~place~to~visitdtm <- DocumentTermMatrix(dd, control = list(weighting = weightTfIdf))as.matrix(dtm)这将产生
# Docs good~restaurent nice~place~to~visit very~bad very~good you~are~great# D1 0.0000000 0.0000000 0 0.3333333 0.3333333# D2 0.3333333 0.3333333 0 0.0000000 0.0000000如果我从csv文件加载document，那么每个文档的第一个词会被连接起来，如下所示：
> file_loc <- "testdata.csv"> require(tm) Loading required package: tm> x <- read.csv(file_loc, header = FALSE)> x <- data.frame(lapply(x, as.character), stringsAsFactors=FALSE)> dd <- Corpus(DataframeSource(x))> dd <- tm_map(dd, stripWhitespace)> dd <- tm_map(dd, tolower)> dd <- tm_map(dd, function(x) { PlainTextDocument( gsub("\\s+","~",strsplit(x,",\\s*")[[1]]), id=ID(x) ) })> inspect(dd)只连接了第一个词，如下所示：
# $D1# very~good# # $D2# very~bad如何连接所有词并创建如上所示的DocumentTermMatrix？
回答：
你读取数据的方式不正确。我使用scan来读取。以下方法有效：
docs <- scan("testdata.csv", "character", sep = "\n")dd <- Corpus(VectorSource(x))dd <- tm_map(dd, function(x) { PlainTextDocument( gsub("\\s+","~",strsplit(x,",\\s*")[[1]]), id=ID(x) )})inspect(dd)dtm <- DocumentTermMatrix(dd, control = list(weighting = weightTfIdf))as.matrix(dtm)