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Thanks to those who responded. I was wondering if taking a bag of words
approach might work. For example chunking the sentences to be analyzed and
running a Lucene query against an index storing sentiment polarity. Has anyone
had success with this approach? I do not need a super accurate system,
something that is "reasonably" accurate.
Also, could you suggest good publicly available training datasets? I am aware
of the Cornell Movie Reviews dataset[1]
Thanks
AS
[1] http://www.cs.cornell.edu/people/pabo/movie-review-data/
----- Original Message ----
From: Vivek Balaraman <vivek.balaraman@xxxxxxxxx>
To: java-user@xxxxxxxxxxxxxxxxx
Sent: Saturday, March 1, 2008 6:35:04 AM
Subject: Re: Lucene for Sentiment Analysis
We've been working on Sentiment Analysis. We use GATE and Wordnet for the
lexical / semantic analysis and J Free Charts for the visualization. The
domain is reviews on retail banking and in general our accuracy is around
75% and recall around 25%
We tried out lingpipe as well which also gave good results.
Tx
Vivek Balaraman
On Sat, Mar 1, 2008 at 3:16 AM, Aaron Schon <aaron_schon@xxxxxxxxx> wrote:
> Hello, I was interested to learn about using Lucene for text analytics
> work such as for Sentiment Analysis. Has anyone done work along these lines?
> if so, could you share your approach, experiences, accuracy levels obtained
> etc.
>
> Thanks,
> AS
>
>
>
>
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