Actually I think I just may have invented one possible way to do that
using a lossless probabilistic model in my previous email to this list.
Did you read it?
:-) I read it. I think that you have to be in a "perfect world" situation
for what you propose to be feasible (i.e. it requires seeing the phrases in
pretty much identical contexts -- which you have to recognize as
identical -- and then being able to tell that that they affect the
distribution of following words and phrases approximately equivalently --
which is an equally large problem). I'm afraid that it *really* does not
look like a *feasible* solution at all (to me -- as I said, I think that
going at all this via a probability model is not the way to go since it
entails getting and analyzing those probabilities from far less data than I
think is necessary for those operations).
Mark
----- Original Message -----
From: "Sampo Etelavuori" <[EMAIL PROTECTED]>
To: <agi@v2.listbox.com>
Sent: Monday, August 28, 2006 8:56 AM
Subject: **SPAM** Re: [agi] Lossy *&* lossless compressi
On 8/28/06, Mark Waser <[EMAIL PROTECTED]> wrote:
How does a lossless model observe that "Jim is extremely fat" and "James
>continues to be morbidly obese" are approximately equal?
Actually I think I just may have invented one possible way to do that
using a lossless probabilistic model in my previous email to this list.
Did you read it? Anyway, in case you have a hard time figuring it out all
by yourself, the idea behind it can be pretty straigthforwardly
generalized to be used with phrases and thus I think phrases can be
observed to be approximately equal if they can occur in pretty much
identical contexts and affect the distribution of following words and
phrases approximately equivalently.
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