Semantic Web and Knowledge Representation: Sharath Srinivas CMSC 818Z, Spring 2007 Semantic Web and Knowledge Representation


Outline: Outline Motivation Introduction Information centric perspective of semantic web Architecture of the Semantic Web Future Video and examples!


Motivation: 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! Why is it so? All Computers do is what they are programmed to do! This is the state of affairs today


Motivation…: 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: 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: 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…: Response…


Intelligent Search: 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?: 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 Dynamics Information Representation Information Representation Loss During transformation into its Representation ?


Information Dynamics: Information Dynamics Ideal Scenario Information Dynamics… Information Representation Information Representation Will this ever be possible?


Semantic: Semantic semantic, a. and n. a. Relating to signification or meaning.


Semantic…: Semantic… Making web pages machine readable Combining information from multiple sources Making inferences to find new knowledge


Semantic Web…: Semantic Web… My Web Page (which is a autonomous intelligent agent) should determine whom I should meet and at what time.


Wedding Cake!: Wedding Cake!


Pieces of the 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: XML: User definable and domain specific markup HTML: Introduction to AI Teacher: Frank van Harmelen Students: 1AI, 1I Requirements: none Introduction to AI Frank van Harmelen 1AI, 1I none XML:


XML document= labelled trees: XML document= labelled trees ... ... ... ... ...


Syntax versus Semantics: 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…: RDF…


RDF…combining Information: RDF…combining Information


RDF…combining Information: RDF…combining Information RDF…combining Information


RDF…combining Information: RDF…combining Information


RDF…combining Information: RDF…combining Information


Wedding cake…: Wedding cake…


RDF SChema: RDF SChema


Slide28: Wedding cake…


Ontology: 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 : Ontology…example Person Student Researcher subClassOf subClassOf Jeen type hasSuperVisor domain range Frank type hasSuperVisor


Ontology: 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: What you can do Mark up web pages Present databases as RDF Use and develop new ontologies


Wedding cake…: Wedding cake…


Logic, Proof and Reasoning: Logic, Proof and Reasoning


Wedding cake…Revisited!!: Wedding cake…Revisited!! Proof, Logic and reasoning are active areas of research


Trust : Trust Self Intelligent agents: Can we trust them? Don’t drive! Weather is bad Should I trust my agent?


Conclusion: Conclusion Semantic web is no hype Its already a reality It is and it will continue to make Computers less dumb!


References and Resources: 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