So let's look at the vision that Tim Berners-Lee [UNKNOWN] way back in 2000
called the semantic web, which essentially puts together some of the ideas that we
have been talking in the past few minutes. So to answer a, a question or query like ,
who is the leader of USA, a semantic web system or web intelligent system
incorporating semantics would proceed something like as follows: we might
imagine a site a.com which collects facts by processing lots of web data,
As we shall see later in this week how that's done. So we get facts like Obama is
President of U.S.A., Vladimir Putin is president of Russia, Pranab Mukherjee is
president of India, Manmohan Singh is Prime Minister of India, and many other
facts about presidents, premiers, prime ministers, etc.
Another site might be extracting information about who is leader of which
country might figure out that Manmohan Singh is leader of India, Zuma is leader
of South Africa, Putin is leader of Russia, and so on.
A third site now might combine. Facts from a.com and b.com, and come to a
conclusion using rule earning that with some degree of confidence that if x is the
president of c, than x is leader of c. The process by which a bunch of facts is
generalized to a rule using techniques like rule mining that we have seen earlier
is called inductive reasoning, as opposed to deductive reasoning, which is normal
logical inference. Inductive reasoning is almost always
probabilistic to a certain extent. Using some of the techniques that we've
already seen. Next normal deductive reasoning allows us
to combine the rules and facts to arrive at.
The fact that Obama is the leader of the U.S.A., which is then the answer to our
query. Further, this new fact is then added back
to the appropriate part of the semantic way of dealing with facts of this nature.
Now this vision, is a powerful vision expressed more than a decade ago.
It's not exactly been realized today, but, much of the technology needed, to express
facts and rules, in a form that can be shared, across, different, systems.
Using XML languages such as RDFS, RD, we just call it RDF schema, and OWL or the
Web Ontology Language. That technology has been developed by the
World Wide Web Foundation, where Tim Berners-Lee plays an important role.
So the web of data and semantics is in principle possible.
The question is, who is populating this web.
Web scale inference is in some sense also possible,
Not necessarily happening in exactly the same way as initially envisioned.
But is happening. With efforts such as Google Squared, if
you just figured this out from the web. It's essentially Google's attempt to
extract lots of different facts from the wide, the world wide web.
Wolfram Alpha is another recent search engine which relies on learning lots of
facts about the world. And, of course, there's Watson which we've
come across earlier , the IBM program that won the Jeopardy challenge.
These are efforts which don't necessarily use techniques like OWL and semantic web
technologies. Though they have a similar intent in
spirit, which is essentially to learn facts from the web and be able to reason
about those facts in a web intelligence system, as opposed to merely searching for
web pages. So to summarize, the Symantec web vision
is about a web of data and semantics. Which is shared so that one can have
inference or reasoning at web scale. A bunch of technologies which is designed
to enable this, RDF or Resource Description Framework as it's expansion is
the Web Ontology Language and various variance of that, as we can see very soon.
These are all technologies designed to enable this sharing of data and semantics
across the web. At the same time,
They are use to actually perform reasoning, has not necessarily proceeded
in exactly the same way as originally envisioned.
Google Squared, Wolfram Alpha, Watson do in fact reason using facts learned from
the web, but not necessarily using the same technology backbone.
We shall return to the semantic web and some efforts which are in fact learning
facts in RDF and OWL form a little later. For the moment let's turn to resolution
and logic and how such deductive reasoning might actually take place within a
semantic web engine, regardless of the exact technology it uses.