Fixed models based on output from graph.py script and comments on
http://groups.google.com/group/melange-soc-dev/browse_thread/thread/fb532a7db1f19ea7
# Performance note: I benchmarked this code using a set instead of
# a list for the stopwords and was surprised to find that the list
# performed /better/ than the set - maybe because it's only a small
# list.
stopwords = '''
i
a
an
are
as
at
be
by
for
from
how
in
is
it
of
on
or
that
the
this
to
was
what
when
where
'''.split()
def strip_stopwords(sentence):
"Removes stopwords - also normalizes whitespace"
words = sentence.split()
sentence = []
for word in words:
if word.lower() not in stopwords:
sentence.append(word)
return u' '.join(sentence)