Semantic Web and Knowledge
Representation
Sharath Srinivas
-
CMSC 818Z, Spring 2007
Department of Computer Science,
University of Maryland, College Park
1
Outline

Motivation

Introduction

Information centric perspective of
semantic web

Architecture of the Semantic Web

Future

Video and examples!
Motivation

Is there any such task that a computer can do, which a
human cannot do? …

5 possible answers:
Yes, of course!
 Not at all
 Sort of, but most tasks that humans do cannot be done by
computers.
 Sort of, but most tasks that humans do can be done by
computers
 No Comments!
This is the state of
All Computers do is what they are
affairs today
 Why is it so?
programmed
to do!

Motivation…

So, are computers dumb?

Yes…sort of!

Then why are we (Computer Scientists)
spending our life on something that’s dumb?

To make them less dumb!!!
Introduction

The Web is considered to be the most
powerful information tool in history.

One of the most difficult resources to search
and evaluate

“The ultimate goal of the Web will be achieved
when search engines can find the answer to
the question of Life, the Universe and
Everything else - obviously that will occur in
Web 42.0” –Prof. Jim Hendler, MIND lab
Introduction

Web 42.0 ???

What is “Web 42.0”?

What is the current version of the web?

I decided to search for this on google…

No useful results

So I decided to post this question on a forum where
people discuss stuff like this…
Response…
Intelligent Search

So, we need more intelligent search engines, that can
understand the users

Google Answers example:

searching for words isn’t really what you want to do.
You’d like to search for ideas, for concepts, for
solutions, for answers…

Current information representation and retrieval
techniques are not capable of achieving this.
Need of the hour?

We need more intelligent Systems that
can retrieve quality information.

For this we need better representation
techniques of information.

Information is not data, it is knowledge
derived from data.
Information Dynamics
?
Information
Information
Loss During
transformation
into its
Representation
Representation
Representation
Information Dynamics…
Dynamics

Ideal Scenario
Information
Information
Representation
Representation
Will this ever be possible?
Semantic


semantic, a. and n.
a. Relating to signification or meaning.
Semantic…

Making web pages machine readable

Combining information from multiple
sources

Making inferences to find new
knowledge
Semantic Web…
My Web
Page
Advisor 1’s
web Page
Advisor 2’s
web Page
My Web Page (which is a autonomous intelligent agent)
should determine whom I should meet and at what time.
Wedding Cake!
Pieces of the cake…

Parts of the Semantic Web:

A Global naming schema (URI)

A standard syntax for describing data (RDF)

A syntax for representing the properties of
the data (RDF Schema)

A standard means of describing the
relationships between data (OWL)
XML: User definable and domain specific markup

HTML:
<H1>Introduction to AI</H1>
<UL> <LI>Teacher: Frank van Harmelen
<LI>Students: 1AI, 1I
<LI>Requirements: none
</UL>
XML:
<course>
<title>Introduction to AI</title>
<teacher>Frank van Harmelen</teacher>
<students>1AI, 1I</students>
<req>none</req>
</course>
XML document= labelled trees
<course date=“...”>
<title>...</title>
<teacher>...</teacher>
<name>...</name>
<http>...</http>
<students>...</students>
</course>
Syntax versus Semantics

Syntax: the structure of your data

Semantics: the meaning of your data

Two conditions necessary for interoperability:

Adopt a common syntax: this enables applications
to parse the data.

Adopt a means for understanding the semantics:
this enables applications to use the data.
RDF
RDF…
RDF…combining Information
RDF…combining Information

RDF…combining Information
RDF…combining Information
RDF…combining Information
Wedding cake…
RDF SChema
Wedding cake…
Ontology
Ontology
 “... a specification of a
conceptualisation.”
 Vocabulary and relationships
 RDFS
 Classes and subclass relationships
 Properties and subproperty relationships
 Range and domain of properties

Ontology…example
Person
subClassOf
Student
domain
hasSuperVisor
type
Frank
hasSuperVisor
subClassOf
range
Researcher
type
Jeen
Ontology
Identity (owl:sameAs)
 Disjunction
 something can be in one or other class
but not both
 Number restrictions
 at least n of some property
 no more than n of some property
 Flavours: OWLLite, OWLDL,OWLFull

What you can do

Mark up web pages

Present databases as RDF

Use and develop new ontologies
Wedding cake…
Logic, Proof and Reasoning
Wedding cake…Revisited!!
Proof, Logic and reasoning are active areas of research
Trust

Self Intelligent agents: Can we trust
them?
Don’t drive!
Weather is bad
Should I trust
my agent?
Conclusion

Semantic web is no hype

Its already a reality

It is and it will continue to make
Computers less dumb!
References and Resources

MindLabs and Mindswap: Google it!

Wikipedia: Google Search: Semantic web Wiki

The talk given by Hugo Mills at the Hampshire
Linux Users group: Cannot find using google…

www.hantslug.org.uk/cgi-bin/wiki.pl?TechTalks/3rdJune2006