Corrections to brown_ic.py by Jordan Boyd-Graber <jbg@cs.princeton.edu>, to fix the following problems:
Corrections to brown_ic.py by Jordan Boyd-Graber <jbg@cs.princeton.edu>,
to fix the following problems:

1. Doesn't do Laplace smoothing for unobserved terms (only does it for
observed terms, which is really bizarre)
2. Can get stuck in an infinite loop if a cycle exists in the WordNet
data
3. Assumes a sense/synset distinction that no longer exists in the
NLTK WordNet package
4. Assumed (incorrectly) the case of POS tags in the Brown corpus
5. Is wasteful of memory (dictionaries are keyed by synset objects
rather than by offsets)
6. The time to propagate counts is based on the total size of WN, not
the number of synset counts observed. So even if the corpus is very
small, it takes forever to compute.




svn/trunk@5970

nltk/nltk,nltk/nltk,nltk/nltk