I am trying to do some very basic text analysis with the tm package and get some tf-idf scores; I'm running OS X (though I've tried this on Debian Squeeze with the same result); I've got a directory (which is my working directory) with a couple text files in it (the first containing the first three episodes of Ulysses, the second containing the second three episodes, if you must know).
R Version: 2.15.1 SessionInfo() Reports this about tm: [1] tm_0.5-8.3
Relevant bit of code:
library('tm')
corpus <- Corpus(DirSource('.'))
dtm <- DocumentTermMatrix(corpus,control=list(weight=weightTfIdf))
str(dtm)
List of 6
$ i : int [1:12456] 1 1 1 1 1 1 1 1 1 1 ...
$ j : int [1:12456] 2 10 12 17 20 24 29 30 32 34 ...
$ v : num [1:12456] 1 1 1 1 1 1 1 1 1 1 ...
$ nrow : int 2
$ ncol : int 10646
$ dimnames:List of 2
..$ Docs : chr [1:2] "bloom.txt" "telemachiad.txt"
..$ Terms: chr [1:10646] "_--c'est" "_--et" "_--for" "_--goodbye," ...
- attr(*, "class")= chr [1:2] "DocumentTermMatrix" "simple_triplet_matrix"
- attr(*, "Weighting")= chr [1:2] "term frequency" "tf"
You will note, that the weighting appears to still be the default term frequency (tf) rather than the weighted tf-idf scores that I'd like.
Apologies if I'm missing something obvious, but based on the documentation I've read, this should work. The fault, no doubt, lies not in the stars...