Hi all,
I have been playing with a very crude approach to this problem
(extraction of boilerplate and other furniture such as
header/footer/navigation panels), which I don't think anyone has
mentioned here yet...
First I extract the text from the HTML (I use lynx -dump for this).
Next I count the number of times every line in the collection of files
occurs. Then I (manually) scan through the generated list and set a
more or less arbitrary threshold for filtering out the stuff I don't
want, e.g. any line that occurs more than 10 times (keeping an eye out
for lines which may have a high frequency for some other reason).
This edited list is then used as a filter - all lines which feature in
it are deleted from the collection of files.
Despite its dirtiness, this might have certain advantages. It seems to
work quite robustly and is very quick (at least, for modest corpora of
~1 million words). It allows you to remove things like "More >>" links
which often occur at the end of paras, rather than in header/footer or
navigation panels. Moreover, you are able to keep information about the
frequency of boilerplate and furniture elements, while filtering them
out of the main corpus.
On the down side, it requires tailoring to each website from which you
wish to collect data - which in our specific case happens not to be a
problem. Some revision would be necessary if the corpus were to be
updated with new material from a previously collected site. It is also
likely that some things are cut which you might want to keep (e.g.
frequent subheadings, which occur on many pages, whilst not coming under
header/footer/navigation panel categories). Similarly, some unwanted
text gets through.
On the whole it seems to work well enough for us, though.
Best,
Martin Thomas
Centre for Translation Studies
University of Leeds
PS - I hope this message doesn't appear twice - sorry if it does - I
originally sent it from a non-member email account.
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