问题
I have a list of phrases and a corpus of documents.There are 100k+ phrases and 60k+ documents in the corpus. The phrases are might/might not present in the corpus. I'm looking forward to find the term frequency of each phrase present in the corpus.
An example dataset:
Phrases <- c("just starting", "several kilometers", "brief stroll", "gradually boost", "5 miles", "dark night", "cold morning")
Doc1 <- "If you're just starting with workout, begin slow."
Doc2 <- "Don't jump in brain initial and then try to operate several kilometers without the need of worked out well before."
Doc3 <- "It is possible to end up injuring on your own and carrying out more damage than good."
Doc4 <- "Instead start with a brief stroll and gradually boost the duration along with the speed."
Doc5 <- "Before you know it you'll be working 5 miles without any problems."
I am new to text analytics in R and have approached this problem on the lines of Tyler Rinker's solution to this R Text Mining: Counting the number of times a specific word appears in a corpus?.
Here's my approach so far:
library(tm)
library(qdap)
Docs <- c(Doc1, Doc2, Doc3, Doc4, Doc5)
text <- removeWords(Docs, stopwords("english"))
text <- removePunctuation(text)
text <- tolower(text)
corp <- Corpus(VectorSource(text))
Phrases <- tolower(Phrases)
word.freq <- apply_as_df(corp, termco_d, match.string=Phrases)
mcsv_w(word.freq, dir = NULL, open = T, sep = ", ", dataframes = NULL,
pos = 1, envir = as.environment(pos))
When I'm exporting the results in csv, it is only giving me whether phrase 1 is present in any of the docs or not.
I'm expecting an output as below (excluding the non-matching phrases):
Docs Phrase1 Phrase2 Phrase3 Phrase4 Phrase5
1 0 1 2 0 0
2 1 0 0 1 0
回答1:
I tried with your approach and can't replicate:
Using:
library(tm)
library(qdap)
Docs <- c(Doc1, Doc2, Doc3, Doc4, Doc5)
text <- removeWords(Docs, stopwords("english"))
text <- removePunctuation(text)
text <- tolower(text)
corp <- Corpus(VectorSource(text))
Phrases <- tolower(Phrases)
word.freq <- apply_as_df(corp, termco_d, match.string = Phrases)
mcsv_w(word.freq, dir = NULL, open = T, sep = ", ", dataframes = NULL,
pos = 1, envir = as.environment(pos))
I get the following csv:
docs word.count term(just starting) term(several kilometers) term(brief stroll) term(gradually boost) term(5 miles) term(dark night) term(cold morning)
1 7 1 0 0 0 0 0 0
2 12 0 1 0 0 0 0 0
3 7 0 0 0 0 0 0 0
4 9 0 0 1 1 0 0 0
5 7 0 0 0 0 0 0 0
来源:https://stackoverflow.com/questions/29397235/matching-a-list-of-phrases-to-a-corpus-of-documents-and-returning-phrase-frequen