I remember when Nevill-Manning and Witten came out with the SEQUITUR
compression algorithm and was bemused by their motivation:  Search Indexing.

I'm not sure of the intellectual genealogy relating their work to fellow
Kiwi, Shane Legg'.  When I contacted Nevill-Manning regarding the initial
announcement of the Hutter Prize, he was at Google in NYC.  My hope was
he'd be able to help guide Google to see the value of underwriting it.  But
I was disappointed that he wasn't working on search or compression so much
as he was something to do with Google's attempt to get into the online
retail business.   Very soon thereafter that Google released its N-gram
databases -- and I believe he had a hand in that -- but that is hardly the
stuff of Wikipedia as benchmark corpus.

On Sun, Jul 19, 2020 at 3:35 PM Matt Mahoney <[email protected]>
wrote:

> Search is a compression problem. You want to find the response (as
> training data) that best compresses the query.
>
> On Sun, Jul 19, 2020, 11:01 AM stefan.reich.maker.of.eye via AGI <
> [email protected]> wrote:
>
>> I have a first search engine on top of the compressor that actually works
>> <http://code.botcompany.de/1029098>. Tested it with all possible texts &
>> queries of up to length 7 over a 3-letter alphabet
>> <http://code.botcompany.de/1029104>, so I think it's ok.
>>
>> However, it goes through the query character by character and does not
>> compress it first. That's quite certainly not the most effective way. So we
>> should put the query through the compression algorithm first.
>>
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