http://en.wikipedia.org/wiki/Watson_%28computer%29
has a nice summary of Watson but not much in depth technical
details.
It does include a
long list of references so it is a good
starting point.
<quote>
The sources of information for Watson include encyclopedias,
dictionaries, thesauri, newswire articles, and literary works.
Watson also used databases, taxonomies, and ontologies.
Specifically, DBPedia, WordNet,
and Yago were used.
The IBM team provided Watson with millions of documents,
including dictionaries, encyclopedias, and other reference
material that it could use to build its knowledge.
Although Watson was not connected to the Internet during the
game,
it contained 200 million pages of structured and unstructured
content consuming four terabytes of disk storage,
including the full text of Wikipedia.[9]
</quote>
I am not sure that you can get much bigger in terms of big data or
human knowledge in a machine readable form.
Although it included ontologies, it does not restrict itself to
only processing data in nice neat formats.
It certainly does not care much about the niceties of strict logic
processing except as a tool for guiding more human-like analysis
of unstructured data.
It is fast and can beat humans most of the time on general
knowledge questions.
It is based on current hardware but the software is organized into
multiple parallel processing paths to get the speed.
http://laplacian.wordpress.com/2011/02/27/how-ibms-watson-computer-thinks-on-jeopardy/
is another nice short overview.
Ron
On 30/01/2014 4:58 PM, Jack Ring wrote:
Christophe,
As I have posted previously, if you are going to make BigData serve me then your first focus must be on describing me, my ontology and ontogeny. This is far beyond enabling me to express a query and experience 80% false positives and false negatives.
Once you have enabled a semantic model of me then a machine can find any and all instances in Big Data that are relevant to me. Further, if you give me the ability to express a time-based interest profile and the ability to state what data is NOT of interest (so it can be ignored at the source) then your machine will have done me a big enough service that I will be willing to use it and even reward you for the service.
This approach has been used for years but is not well known because if you use a stored program computer it won't scale.
If you use an another kind of technology now almost available then it will work quickly and cheaply.
Unfortunately for the Ontology Summit the leaders do not want to be bothered with "hardware" considerations so you will have to hobble along with hundred-year-old automata.
Onward,
Jack Ring
On Jan 30, 2014, at 12:47 PM, Christoph LANGE wrote:
Dear all,
after the end of a great session on "making use of ontologies – tools,
services, techniques", with inspiring input by TillMossakowski,
ChrisWelty and AlanRector (thanks once more to all speakers!), the
discussion is really just starting…
Polemically one could argue that real-world services like Watson need
Big Data (such as common human knowledge), and they need ontologies in
the sense of some structured way of processing Big Data – but do they
need (formal) ontology _languages_?
In the more formal world we see that OWL 2 offers much more alternatives
for modeling knowledge-rich applications than OWL 1, I'm personally not
aware of plans towards OWL 3, and in the formal world there are also
translations between OWL and representations such as UML, which may
appeal better to humans and has complementary tool support – but to what
extent are these formalisms related to what humans think and know and
how they use language?
In short: facing the reality of Big Data and the need for increasingly
intelligent services, (how) can ontology-based tools and techniques help?
Cheers,
Christoph
--
Christoph Lange, Enterprise Information Systems Department
Applied Computer Science @ University of Bonn; Fraunhofer IAIS
http://langec.wordpress.com/about, Skype duke4701
→ Semantic Publishing Challenge: Assessing the Quality of Scientific Output
ESWC, 25–29 May 2014, Crete, Greece. https://tinyurl.com/SPChallenge14
Abstract submission until 7 March.
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