On 2/16/11 11:29 AM, John F. Sowa wrote:
This was not the problem.
>
> Watson has Wikipedia in its memory. The answers to the specified
> question are in Wikipedia: Toronto being a Canadian city, Chicago
> being a US city, Chicago having O'Hare and Midway as airports,
> O'Hare being named after a WW II hero (flying ace), Midway being the
> name of a WW II battle.
I strongly agree with Doug. Watson has predigested 15 terabytes
of background knowledge, which is tailored and indexed for its own
representations. Google's search methods are much less precise,
and they only return entire documents, which Watson would have
to spend too much time to read and analyze before it could answer
a jeopardy question.
Watson has DBpedia and other LOD community curated datasets etc.
in memory.
It's a triumph of many things:
1. Structured Linked Data -- in a Property Graph Model DBMS (a
Deductive Database system)
2. NLP -- covered amply by John
3. Machine Learning -- ditto .
Take out one of these pieces, and the algorithms (what puts the
above to good use) will fall apart and Watson will loose the
dexterity of its mind :-)
Sadly, #1-3 haven't always worked together. Watson demonstrates --
successfully -- why they should.
--
Regards,
Kingsley Idehen
President & CEO
OpenLink Software
Web: http://www.openlinksw.com
Weblog: http://www.openlinksw.com/blog/~kidehen
Twitter/Identi.ca: kidehen
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