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Transcript of The Semantic Web Presented by Zhimin Chen. HTML Is Human Readable, Not Machine understandable A...
The Semantic Web
Presented by Zhimin Chen
HTML Is Human Readable, Not Machine understandable A Course Schedule Web Page
Consequence: agents can’t effectively process information on the web automatically
XML May Help, But Can Only Help XML fragment for the course
schedule…<course-offered>
<catalog> 92809 </catalog><course>
<number> 500 </number><session> 201 </session><name> Algorithm Design </name>
</course><room> cisr 104 </room><instructor> Evans </instructor>
…
XML May Help, But Can Only Help (Cont’d) Tags in XML carry no semantics
<course><ID> 500 </ID><Session> 201 </Session><Name> Algorithm Design </Name>
</course>
<H1><H2> 500 </H2><H3> 201 </H3><H4> Algorithm Design </H4>
</H1>
is no more meaningful than
Expressing Meanings Of Tags Semantic network, a graph composed of
Two Kinds of Nodes Taxonomic categories or property (labeled by
relation constants) Objects in the domain (labeled by object constants)
Three Kinds of Arcs IS-A arc Set membership arc Function arc
Meanings of tags as taxonomic concepts or property
Example Of Semantic Network
[Tim Berners-Lee, James Hendler and Ora Lassila]
Use Case – Precise Search Current search engine
Key word based Single page only
Semantic search Assemble knowledge spanning many pages
Example Scenario: locating a person her last name is "Cook“ she works for a company on your client list she has a son attending your alma mater,
Avondale University
Architecture Of The Semantic Web
[Tim Berners-Lee]
Where the standard
progress stands
Outline of the talk RDF and RDF Schema DAML+OIL and OWL Description Logic
RDF An RDF statement is a triple
<subject, property, value> Reification is statement about
statement, i.e., subject is a statement
Each subject identified by a URI Semantics represented as a set of
triples and serialized as XML
RDF Example
http://www.bob-stacy.com/cook
http://www.bob-stacy.com
<rdf:Description rdf:about=“http://www.bo
b-stacy.com/cook”><works-for
rdf:resource=“www.bob-stacy.com” />
</rdf:Description>
<rdf:Description rdf:about=“http://w
ww.bob-stacy.com/cook”>
<lives-in>Johannesburg</
lives-in> </rdf:Description>
RDF Schema RDF schema provides a way to define the
meanings of tags A tag is a class
Employee rdf:type rdf:class <rdf:Description rdf:ID="Employee">
<rdf:type rdf:resource = "http://www.w3.org/2000/01/rdf-schema#Class"/> </rdf:Description>
A tag is a property Works-for rdf:type rdf:property Works-for rdf:domain Employee Works-for rdf:range Company
RDF Schema (Cont’d) XML as a shorthand for RDF
descriptions of a semantic network
Class ClassProperty
Employee Company
type
type
Works-forrangedomain
type
Mrs. Cook Bob-StacyWorks-for
type
type
RDF Schema (Cont’d)
<Company rdf:ID=“Bob-Stacy” /><Employee rdf:ID=“Cook”>
<Works-for rdf:resource=“#Bob-Stacy” />
</Employee>
RDF Schema (Cont’d) Other modeling mechanisms
Rdf:subClassOf Rdf:subPropertyOf Rdf:container and Rdf:collection Reification (rdf:type is rdf:statement)
daml+oil provides more
Outline of the talk RDF and RDF Schema DAML+OIL and OWL Description Logic
DAML+OIL DAML+OIL adds richer expressive
mechanism to RDF schema Constraints on properties Boolean combination of classes Equivalence and disjointness Property of property
Constraints On Property A class is defined as all objects
satisfying constraints on property Universal constraint
E.g.: All objects working for companies<daml:restriction>
<daml:onProperty rdf:resource=“#works-for” />
<daml:toClass rdf:resource=“#Company” /></daml:restriction>
Existential constraint (hasClass and hasValue)
Constraints On Property (Cont’d)
Cardinality constraint (minCardinality, maxCardinality, exactCardinality)
E.g.: All objects having more than 1 child<daml:restriction>
<daml:onProperty rdf:resource=“#parentOf” />
<daml:minCardinality> 2 <daml:minCardinality/></daml:restriction>
Boolean Combination of Classes Intersection, union, complement
E.g.: all objects working for Bob-Stacy and having more than 1 child<daml:Class ID=“BobStacyParentWorker”>
<daml:intersectionOf daml:parseType=“daml:collection”><daml:restriction><daml:onProperty rdf:resource=“#works-for” /><daml:hasValue rdf:resource=“#Bob-Stacy” /></daml:restriction> <daml:restriction><daml:onProperty rdf:resource=“#parentOf” /><daml:minCardinality> 2 <daml:minCardinality/></daml:restriction></daml:intersectionOf>
</daml:Class>
Equivalence and Disjointness Equivalence
sameClassAs samePropertyAs sameIndividualAs
Disjointness disjointWith differentIndividualFrom
Property of property inverseOf transitiveProperty uniqueProperty and
unambiguousProperty
OWL OWL DL DAML + OIL
Add/remove/rename some language constructs
Version management Knowledge modularization (import)
OWL Full allows class to be an individual (undecidable)
Outline of the talk RDF and RDF Schema DAML+OIL and OWL Description Logic
ALC Concept descriptions are formed
using constructs: A (atomic concept) C D (daml:intersectionOf) C D (daml:unionOf) C (daml:complementOf) R.C (daml:toClass) R.C (daml:hasClass)
SHIQ ALC plus
Transitive role R* (daml:transitiveRole)
Concept hierarchy and role hierarchy (subClass and subProperty)
Inverse role R- (daml:inverseOf)
Qualified number restriction nR, etc (daml:minCardinality, etc)
Basic Inference Problem Concept subsumption C T D Reduction to unsatisfiability
C T D there exists no model I for T s.t. (C D)I is not empty.
Tableau algorithm to find such a model
Tableau D is a concept sub(D) is the closure of concept
subexpressions in D’s definition S is a set of individuals L : S 2sub(D) maps each individual to a
subset of sub(D) E : R 2SS maps each role to a set of
pairs of individuals There is some s in S s.t. D is in L(s)
Tableau For ALC Concepts T=<S, L, E> is a tableau for ALC concept
D if it holds L(s) does not contain both C and C If C E L(s), then C L(s) and E L(s) If C E L(s), then C L(s) or E L(s) If R.C L(s) and <s,t> E(R), then C L(t) If R.C L(s), then there is some s s.t. <s,t>
E(R) and C L(t) Further constraints for other concept
constructs can be added for more expressive DL.
Tableau Algorithm For ALC Completion tree
Node x labeled with a set L(x) sub(D) Edge <x,y> labeled with a set L(<x,y>) of
roles occurring in D Tree expansion rules
- rule: Condition: C1 C2 L(x) and {C1, C2} L(x) Action: L(x) {C1, C2} L(x)
- rule: Condition: C1 C2 L(x) and {C1, C2} L(x) = Action: for some C {C1, C2} , L(x) {C} L(x)
Tableau Algorithm For ALC (Cont’d)
- rule: Condition: R.C L(x) and there is a R-
successor y of x s.t. C R Action: L(y) {C} L(y)
- rule: Condition: R.C L(x) and x has no R-
successor y s.t. C L(y) and no other rule is applicable to any of its ancestors
Action: create a R-successor y for x with L(<x,y>)=R and L(y)={C}
Tableau Algorithm For ALC (Cont’d) A node has clash if {C, C} L(x) Algorithm starts with a node x
labeled with L(x)={D} Applying expansion rules until
A clash happens No rules can be further applied to the
tree
Tableau Example Check (R.A) (R.B) R.(A B) D = (R.A) (R.B) (R.(A
B))x{(R.A) (R.B) (R.(A B))}{(R.A), (R.B), (R.(A B))}
y
R
{A}{A, (A B)}{A, A}
clash {A, B} z
R
{B}{B, A B}
{B, A }
Transitive Role and Blocking + - rule:
Condition: R.C L(x) where R is a transitive role and there is a R-successor y of x s.t. R.C L(y)
Action: L(y) {R.C} L(y) May lead to infinite loop Subset blocking: if L(y) is a subset
of an ancestor’s label L(x), then block the expansion
Blocking Example
xL(x)={C, R.C, R.(R.C)}
y
R
L(y)={C}L(y)={C, R.C}
L(x)={C, R.C, R.(R.C)}
Blocked
More Expressive DL For additional concept construct
(inverse role, quantifier, etc.), add more expansion rules and blocking rules
Optimizations Backjumping
L(x)={C1 D1, …, Cn Dn, R.(A B), R.(A)}
[Horrocks-Satter-Tobies]
backjumping
pruning
Optimizations (Cont’d) Absorption
Reasoning w.r.t. axiom C D needs to add (C D) to every node
CN D (CN D) only need to add D (D) to the nodes that contain CN (CN)
Transforming axiom into this form CN C D CN C D CN C, CN D CN C D Similar rules for the cases
Optimizations (Cont’d) Cache
Cache the satisfiability of L(x) for node x
Caching partial tableaus of concepts to check obvious satisfiability (E.g., merge the tableau of C and D to check satisfiability of C D (and thus C D))
Optimizations (Cont’d) Lazy expansion of concept Semantic branching search C1, …, Cn, C1 … Cn D D Heuristic guided search
Oldest-first: select the disjunctions dependent on the least recent branching point
Summary The semantic web tries to make www
machine accessible OWL is the current standard to define
vocabulary, and a large part of OWL is DL Challenges (DB-related)
Scalibility (techniques of reasoning with individual in DL unlikely can scale up)
Query Ontology design and integration
References W3C standards:
Resource Description Framework (RDF) Model and Syntax Specification W3C Recommendation 22 February 1999 Ora Lassila, Ralph R. Swick, eds. http://www.w3.org/TR/1999/REC-rdf-syntax-19990222/
RDF Vocabulary Description Language 1.0: RDF Schema W3C Working Draft Dan Brickley, R.V. Guha, eds. http://www.w3.org/TR/rdf-schema/
RDF Primer W3C Working Draft Frank Manola, Eric Miller, eds. http://www.w3.org/TR/rdf-primer/
DAML+OIL (March 2001) Reference Description. Dan Connolly, Frank van Harmelen, Ian Horrocks, Deborah L. McGuinness, Peter F. Patel-Schneider, and Lynn Andrea Stein. W3C Note 18 December 2001. http://www.w3.org/TR/daml+oil-reference
OWL Web Ontology Language Reference W3C Working Draft Mike Dean, Guus Schreiber eds., Frank van Harmelen Jim Hendler Ian Horrocks Deborah L. McGuinness Peter F. Patel-Schneider Lynn Andrea Stein http://www.w3.org/TR/owl-ref/
References (contd.) Description logic:
Basic Description Logics Description Logic Handbook, edited by F. Baader, D. Calvanese, D.L. McGuinness, D. Nardi, P.F. Patel-Schneider, Cambridge University Press, 2002, pages 47-100. http://www.cs.man.ac.uk/~franconi/dl/course/dlhb/dlhb-02.pdf
Practical Reasoning for Very Expressive Description Logics I. Horrocks and U. Sattler and S. Tobies Logic Journal of the IGPL, Volume 8, Issue 3: May 2000. http://www3.oup.co.uk/igpl/Volume_08/Issue_03/pdf/horrocks1.pdf