问题描述
我一直在使用 tm 包来创建一个 DocumentTerm 矩阵,如下所示:
I've been using the tm package to create a DocumentTerm Matrix as follows:
library(tm)
library(RWeka)
library(SnowballC)
src <- DataframeSource(data.frame(data3$JobTitle))
# create a corpus and transform data
# Sets the default number of threads to use
options(mc.cores=1)
c_copy <- c <- Corpus(src)
c <- tm_map(c, content_transformer(tolower), mc.cores=1)
c <- tm_map(c,content_transformer(removeNumbers), mc.cores=1)
c <- tm_map(c,removeWords, stopwords("english"), mc.cores=1)
c <- tm_map(c,content_transformer(stripWhitespace), mc.cores=1)
#make DTM
dtm <- DocumentTermMatrix(c, control = list(tokenize = BigramTokenizer))
现在,DTM 运行良好 - 我想要做的是获取 DTM 中频繁项的频率.显然,我可以使用 findFreqTerms 来获取术语本身,而不是实际频率.termFreq 仅适用于 TextDocument,不适用于 DTM 或 TDM - 有什么想法吗?
Now, the DTM comes out fine - what I want to do is get the frequencies of the frequent terms within the DTM. Obviously, I can use findFreqTerms to get the terms themselves, but not the actual frequencies. termFreq only works on TextDocument, not a DTM or TDM - any ideas?
来自 str 的输出 - 频繁项在 $ 条款中:
Output from str - the frequent terms are in $ Terms:
> str(dtm)
List of 6
$ i : int [1:190] 1 2 3 4 5 6 7 8 9 10 ...
$ j : int [1:190] 1 2 3 4 5 6 7 8 9 10 ...
$ v : num [1:190] 1 1 1 1 1 1 1 1 1 1 ...
$ nrow : int 119
$ ncol : int 146
$ dimnames:List of 2
..$ Docs : chr [1:119] "1" "2" "3" "4" ...
..$ Terms: chr [1:146] "account administrator" "account assistant" "account director" "account executive" ...
- attr(*, "class")= chr [1:2] "DocumentTermMatrix" "simple_triplet_matrix"
- attr(*, "weighting")= chr [1:2] "term frequency" "tf"
推荐答案
感谢 NicE 的建议 - 它运作良好.添加加权参数可以让我在检查 DTM 时得到词频.简单的事情就是对每列求和.
Thanks to NicE for the advice - it works well. Adding in the weighting argument allows me to get out the term frequencies when I inspect the DTM. Simple matter then of summing up per column.
dtm <- DocumentTermMatrix(c, control = list(tokenize = BigramTokenizer, weighting=weightTf))
freqs <- as.data.frame(inspect(dtm))
colSums(freqs)
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