I think the same sort of solution applies to the world series case;
the only difference is that it is semantic features that fail to
combine, rather than syntactic. In other words, there are either zero
associations or none with the potential to count as an answer.

--Abram

On Tue, Jul 29, 2008 at 7:51 PM, Brad Paulsen <[EMAIL PROTECTED]> wrote:
> Matt,
>
> I confess, I'm not sure I understand your response.  It seems to be a
> variant of the critique made by three people early-on in this thread based
> on the misleading example query in my original post.  These folks noted that
> an analysis of linguistic surface features (i.e., the word "fomlepung" would
> not "sound right" to an English speaking query recipient) could account for
> the "feeling of not knowing."  And they were right.  For queries of that
> type (i.e., queries that contained foreign, slang or uncommon words).
>
> I apologized for that first example and provided an improved query (one that
> has valid English syntax and uses common English words -- so it will pass
> linguistic surface feature analysis).  To wit: "Which team won the 1924
> World Series?"
>
> Cheers,
>
> Brad
>
>
> Matt Mahoney wrote:
>>
>> This is not a hard problem. A model for data compression has the task of
>> predicting the next
>
> bit in a string of unknown origin. If the string is an encoding of natural
> language text, then
>
> modeling is an AI problem. If the model doesn't know, then it assigns a
> probability of about
>
> 1/2 to each of 0 and 1. Probabilities can be easily detected from outside
> the model, regardless
>
> of the intelligence level of the model.
>>
>>  -- Matt Mahoney, [EMAIL PROTECTED]
>>
>>
>> -------------------------------------------
>> agi
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>
>
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> agi
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