Domanda

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...

È stato utile?

Soluzione

If you look at the DocumentTermMatrix help page, an at the example, you will see that the control argument is specified this way :

data(crude)
dtm <- DocumentTermMatrix(crude,
           control = list(weighting = function(x) weightTfIdf(x, normalize = FALSE),
                          stopwords = TRUE))

So, the weighting is specified with the list element named weighting, not weight. And you can specify this weighting by passing a function name or a custom function, as in the example. But the following works too :

data(crude)
dtm <- DocumentTermMatrix(crude, control = list(weighting = weightTfIdf))
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