Text answers processing and categorisation

Hi all,

I'm due to program a natural-language categorisation engine soon and could really do with some pointers. The system basically involves people putting in free-text answers to questions and the system must successfully categorise the answers, and then rate them as positive / negative.

eg.

Q: What do you like about this website?
A1: I like the colours.
A2: Content Rocks!
A3: Nothing at all.

I need to categorise the answers into specific areas like layout / content - and tally positive and negative feedback.

This is a rather simplistic example, but if I can develop this then I can expand on the categories etc.

How could I implement this solution? Any ideas?

I've done natural language processing before (computational linguistics) and I've also *heard* about some Bayes theorem stuff, but sadly I wouldn't know where to start with the programming for these. A friend has also mentioned about a content management rating system for another website but I simply don't know where to start researching these issues.

I'm a mssql / c# / vb.net / vb6 developer with lots of experience so ideally I'd love some pointers in these technologies if possible. I'm not great at the maths end of things, so I'd prefer some practical examples of the ideas if possible.

Some source code or even a step-by-step description of a project implemented using these ideas would be absolutely fantastic.

I'm really depending on you for this one guys! Thanks...

Davey.
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DaveyByrneAsked:
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jacobhooverCommented:
In regards to "*heard* about some Bayes theorem stuff" you may want to take a look at www.spambayes.org.  It is a OpenSource Python implimentation of the Bayes theorem for classifying your email as either spam (bad) or ham (good).  If you were to impliment a similar method in your web application, you'd have to "train" it first.  

Hope this helps,
Jake
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DaveyByrneAuthor Commented:
Thanks Jake,

Do you have any experience with the Bayes Theorem? I just need someone to explain it to me in layman's terms - and I reckoned the best way to do this was to look at someone else's implementation.

Sadly this isn't as easy as I thought.

Any chance you could explain it to me in plain english?

thanks,

Dave.
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jacobhooverCommented:
Dave,
  Sorry I have no experience with the theorem itself, but I do know the spambayes implementation works excelent for determining spam.  Issues I can forsee is that while for email we have "ham" and "spam", while in your specification you have a variable number of categories.  I'll grind some more grey matter out tomorrow..

Jake
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DaveyByrneAuthor Commented:
Thanks for the tip anyway Jake.
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