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You can also use RDF reification and old fashioned certainty factors to
cross the bridge :
[Nancy hasVirus #SARS] hasCertainty 0.01
Cheers,
Danny.
> -----Original Message-----
> From: Jonathan Borden [mailto:jonathan@openhealth.org]
> Sent: 26 April 2003 22:17
> To: Mike Champion; xml-dev@lists.xml.org
> Subject: Re: [xml-dev] Statistical vs "semantic web" approaches to
> making sense of the Net
>
>
> Mike Champion wrote:
> >
> > This raises a question, for me anyway: If it will take a "better Google
> > than Google" (or perhaps an "Autonomy meets RDF") that uses Baysian or
> > similar statistical techniques to create the markup that the
> Semantic Web
> > will exploit, what's the point of the semantic markup? Why won't people
> > just use the "intelligent" software directly? Wearing my "XML database
> > guy" hat, I hope that the answer is that it will be much more efficient
> and
> > programmer-friendly to query databases generated by the 'bots containing
> > markup and metadata to find the information one needs. But I must admit
> > that 5-6 years ago I thought the world would need standardized, widely
> > deployed XML markup before we could get the quality of searches that
> Google
> > allows today using only raw HTML and PageRank heuristic algorithm.
> >
> > So, anyone care to pick holes in my assumptions, or reasoning? If one
> does
> > accept the hypothesis that it will take smart software to produce the
> > markup that the Semantic Web will exploit, what *is* the case for
> believing
> > that it will be ontology-based logical inference engines rather than
> > statistically-based heuristic search engines that people will
> be using in
> > 5-10 years? Or is this a false dichotomy?
>
> Yes this is an entirely false dichotomy but you've asked an extremely
> important question.
>
> Forget all the hype that we've been hearing about the SW/AI etc and let's
> look at what the current reality is -- OWL is *fundamentally* about
> classifications. OWL "reasoners" are rightly termed "classifiers" but OWL
> doesn't employ statistics -- a thing is or isn't a member of a class.
>
> To link OWL type classifiers with real world data, there must be
> a leap that
> puts something into a class in the first place and this is where
> statistical-type processors might function. Let's use the
> following example:
> Suppose we have a bunch of noisy binary data about a group of
> people some of
> whom let's say have SARS, some of the data might be audio, some
> video, some
> text etc etc.
>
> Now suppose we have a statistical process that is able to cluster
> individuals together in groups. This processor might emit the following
> class:
>
> <owl:Class rdf:ID="Foo">
> <owl:oneOf rdf:parseType="Literal">
> <ex:person rdf:resource="#Bill"/>
> <ex:person rdf:resource="#Dave"/>
> <ex:person rdf:resource="#Sue"/>
> <ex:person rdf:resource="#Nancy"/>
> <ex:person rdf:resource="#Freddy"/>
> <owl:oneOf>
> </owl:Class>
>
> our reasoner might be able to derive that
>
> <owl:Class rdf:ID="Bar">
> <owl:intersectionOf>
> <owl:Class rdf:resource="#hasCough"/>
> <owl:Class rdf:resource="#hasFever"/>
> <owl:Class rdf:resource="#hasVirus.x233444"/>
> ...
>
> #Foo owl:subClassOf #Bar
>
> and even, in the proper circumstances that...
>
> #Bar owl:sameClassAs #SARS
>
> so the Bayesian/statistical processes might be very well used to
> jumpstart a
> logical classification process that tells us something quite useful.
>
> Jonathan
>
>
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