Yep. Domain adaptation (and dealing with new languages) are as important,
or more important, in NLP as they are in general for other types of
problems that are addressed with machine learning. Once we get better at
injecting better prior information about language (in the general sense)
into our models, maybe that will start looking better.

On Sun, Dec 11, 2011 at 11:04 AM, Josh Patterson <j...@cloudera.com> wrote:

> ok, that makes more sense. I'm not that familiar with how training
> affects NLP, but I am versed in training for general ML purposes ---
> which seems to be the same idea here.
>
> Thanks,
>
> JP
>
> On Sun, Dec 11, 2011 at 9:12 AM, Jason Baldridge
> <jasonbaldri...@gmail.com> wrote:
> > For new domains (e.g. Twitter) and/or new languages, or using more data
> to
> > get a better model. -Jason
> >
> > On Sat, Dec 10, 2011 at 10:07 PM, Josh Patterson <j...@cloudera.com>
> wrote:
> >
> >> working with the examples and reading:
> >>
> >>
> >>
> http://sourceforge.net/apps/mediawiki/opennlp/index.php?title=Sentence_Detector
> >>
> >> I've noticed the section on "Training"; Given that the models already
> >> detect things like sentences and POS, in what circumstances would one
> >> want to "train" the model further?
> >>
> >> Josh
> >>
> >> --
> >> Twitter: @jpatanooga
> >> Solution Architect @ Cloudera
> >> hadoop: http://www.cloudera.com
> >>
> >
> >
> >
> > --
> > Jason Baldridge
> > Associate Professor, Department of Linguistics
> > The University of Texas at Austin
> > http://www.jasonbaldridge.com
> > http://twitter.com/jasonbaldridge
>
>
>
> --
> Twitter: @jpatanooga
> Solution Architect @ Cloudera
> hadoop: http://www.cloudera.com
>



-- 
Jason Baldridge
Associate Professor, Department of Linguistics
The University of Texas at Austin
http://www.jasonbaldridge.com
http://twitter.com/jasonbaldridge

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